U.S. patent number 8,478,388 [Application Number 12/755,359] was granted by the patent office on 2013-07-02 for cardiac coordinate system for motion analysis.
This patent grant is currently assigned to Pacesetter, Inc.. The grantee listed for this patent is Wenbo Hou, Allen Keel, Steve Koh, Thao Thu Nguyen, Kjell Noren, Stuart Rosenberg, Kyungmoo Ryu, Michael Yang. Invention is credited to Wenbo Hou, Allen Keel, Steve Koh, Thao Thu Nguyen, Kjell Noren, Stuart Rosenberg, Kyungmoo Ryu, Michael Yang.
United States Patent |
8,478,388 |
Nguyen , et al. |
July 2, 2013 |
Cardiac coordinate system for motion analysis
Abstract
An exemplary method includes accessing cardiac information
acquired via a catheter located at various positions in a venous
network of a heart of a patient wherein the cardiac information
comprises position information with respect to time for one or more
electrodes of the catheter; performing a principal component
analysis on at least some of the position information; and
selecting at least one component of the principal component
analysis to represent an axis of a cardiac coordinate system.
Various other methods, devices, systems, etc., are also
disclosed.
Inventors: |
Nguyen; Thao Thu (Bloomington,
MN), Noren; Kjell (Solna, SE), Keel; Allen
(San Francisco, CA), Ryu; Kyungmoo (Palmdale, CA),
Rosenberg; Stuart (Castaic, CA), Hou; Wenbo (Lancaster,
CA), Koh; Steve (South Pasadena, CA), Yang; Michael
(Thousand Oaks, CA) |
Applicant: |
Name |
City |
State |
Country |
Type |
Nguyen; Thao Thu
Noren; Kjell
Keel; Allen
Ryu; Kyungmoo
Rosenberg; Stuart
Hou; Wenbo
Koh; Steve
Yang; Michael |
Bloomington
Solna
San Francisco
Palmdale
Castaic
Lancaster
South Pasadena
Thousand Oaks |
MN
N/A
CA
CA
CA
CA
CA
CA |
US
SE
US
US
US
US
US
US |
|
|
Assignee: |
Pacesetter, Inc. (Sylmar,
CA)
|
Family
ID: |
42981503 |
Appl.
No.: |
12/755,359 |
Filed: |
April 6, 2010 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20110092809 A1 |
Apr 21, 2011 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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61167453 |
Apr 7, 2009 |
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Current U.S.
Class: |
600/509; 600/508;
607/17; 607/16 |
Current CPC
Class: |
A61N
1/3627 (20130101); A61B 5/283 (20210101); A61N
1/36542 (20130101); A61N 1/37264 (20130101); A61B
5/7203 (20130101); A61N 1/36842 (20170801); A61N
1/37258 (20130101); A61N 1/3684 (20130101); A61N
1/36535 (20130101); A61N 1/36578 (20130101); A61N
1/36843 (20170801); A61N 1/36521 (20130101) |
Current International
Class: |
A61N
1/00 (20060101); A61B 5/04 (20060101) |
Field of
Search: |
;600/508-509,512
;607/16-17 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
Other References
Abraham, William T. MD et al., "Cardiac Resynchronization in
Chronic Heart Failure," N Engl J Med. Jun. 13, 2002;
346(24):1845-1853. cited by applicant .
Ansalone, Gerardo MD et al., "Doppler Myocardial Imaging to
Evaluate the Effectiveness of Pacing Sites in Patients Receiving
Biventricular Pacing," J Am Coll Cardiol. 2002;39:489-499. cited by
applicant .
Becker, Michael et al., "Impact of left ventricular lead position
on the efficacy of cardiac resynchronization therapy: a
two-dimensional strain echocardiography study," Heart
2007;93:1197-1203. cited by applicant .
Bleeker, Gabe B. MD, PhD et al., "Left Ventricular
Resynchronization Is Mandatory for Response to Cardiac
Resynchronization Therapy: Analysis in Patients With
Echocardiographic Evidence of Left Ventricular Dyssynchrony at
Baseline," Circulation. 2007;116-1440-1448. cited by applicant
.
Chung, Eugene S. MD et al., "Results of the Predictors of Response
to CRT (PROSPECT) Trial," Circulation. 2008;117:2608-2616. cited by
applicant .
Leitman, Marina MD et al., "Two-dimensional Strain--A Novel
Software for Real-time quantitative Echocardiographic Assessment of
Myocardial Function," J Am Soc Echocardiogr. 2004;17:1021-1029.
cited by applicant .
Macias, Alfonso et al., "Left ventricular pacing site in cardiac
resynchronization therapy: Clinical follow-up and predictors of
failed lateral implant," European Journal of Heart Failure.
2008;10:421-427. cited by applicant .
Murphy, Ross T. MD et al., "Tissue Synchronization Imaging and
Optimal Left Ventricular Pacing Site in Cardiac Resynchronization
Therapy," Am J Cardiol. 2006;97:1615-1621. cited by applicant .
Pan, C. et al., "Tissue Tracking Allows Rapid and Accurate Visual
Evaluation of Left Ventricular Function," Eur J Echocardiography.
2001;2:197-202. cited by applicant .
Singh, Jagmeet P. MD et al., "Left ventricular lead electrical
delay predicts response to cardiac resynchronization therapy."
Heart Rhythm. 2006;3:1285-1292. cited by applicant .
Wilton, Stephen B. et al., "Relationship between left ventricular
lead position using a simple radiographic classification scheme and
long-term outcome with resynchronization therapy," J Interv Card
Electrophysiol. 2008;23:219-227. cited by applicant.
|
Primary Examiner: Lavert; Nicole F
Parent Case Text
RELATED APPLICATIONS
This application claims the benefit of U.S. Provisional Application
having Ser. No. 61/167,453, filed Apr. 7, 2009, which is
incorporated by reference herein.
Claims
What is claimed is:
1. A method comprising: providing an electrocardiogram of a
patient; providing position information with respect to time, the
position information acquired via an electrode located in a venous
network of the patient; defining a window based on the
electrocardiogram; and analyzing the position information within
the defined window to determine a time of peak motion of the
electrode wherein the analyzing analyzes the position information
with respect to a cardiac coordinate system.
2. The method of claim 1 wherein the cardiac coordinate system
comprises a cylindrical coordinate system.
3. The method of claim 1 wherein the cardiac coordinate system
comprises a cardiac coordinate system defined at least in part by
at least some of the position information.
4. The method of claim 3 wherein the cardiac coordinate system
comprises a cardiac coordinate system defined at least in part by
one or more of a principal component analysis and a prolate
spheroid model.
5. The method of claim 1 wherein the defining a window comprises
identifying a Q-wave in the electrocardiogram.
6. The method of claim 1 wherein the defining a window comprises
identifying a T-wave in the electrocardiogram.
7. The method of claim 1 wherein the defining a window comprises
defining a window based on a Q-wave and a T-wave.
8. The method of claim 1 wherein the window enhances accuracy in
determination of a time of peak motion of the electrode as being
related to an intrinsic or paced activation of the heart.
9. The method of claim 1 further comprising adjusting a cardiac
therapy based at least in part on the time of peak motion.
10. The method of claim 1 further comprising identifying motion due
to respiration based on a predefined respiratory motion direction
in the cardiac coordinate system.
11. The method of claim 10 wherein defining the respiratory motion
direction comprises performing a principal component analysis.
12. The method of claim 10 wherein the analyzing the position
information comprises accounting for respiratory motion.
13. The method of claim 10 wherein the defining a window comprises
defining a window based on the electrocardiogram and respiratory
motion.
14. One or more non-transitory computer-readable media comprising
processor executable instructions to instruct a computing device
to: access an electrocardiogram of a patient; access position
information with respect to time, the position information acquired
via an electrode located in a venous network of the patient; define
a window based on the electrocardiogram; and analyze the position
information, with respect to a cardiac coordinate system, within
the defined window to determine a time of peak motion of the
electrode.
Description
TECHNICAL FIELD
Subject matter presented herein relates generally to electrode and
lead-based investigation or therapy systems (e.g., cardiac pacing
therapies, ablation therapies, sensing therapies, nerve stimulation
therapies, etc.).
BACKGROUND
Despite advances in device technology, approximately one-third of
patients fail to respond adequately to cardiac resynchronization
therapy (CRT) (see, e.g., Abraham W T, Fisher W G, Smith A L, et
al.: Cardiac resynchronization in chronic heart failure. N Engl J
Med 2002; 346:1845-1853). Left ventricular lead placement is an
important determinant of response, and conventional lead placement
strategy is directed towards targeting the lateral or
posterolateral branches of the coronary venous system (see, e.g.,
Macias A, Gavira J J, Castano S, et al.: Left ventricular pacing
site in cardiac resynchronization therapy: Clinical follow-up and
predictors of failed lateral implant. Eur J Heart Fail 2008;
10:421-427; Wilton S B, Shibata M A, Sondergaard R, et al.:
Relationship between left ventricular lead position using a simple
radiographic classification scheme and long-term outcome with
resynchronization therapy. J Interv Card Electrophysiol 2008;
23:219-227). Despite being a useful approach for positioning leads,
a lack of response still exists in many patients.
Some data suggest that specifically targeting the region of maximal
electrical delay could improve response to CRT (see, e.g., Singh J
P, Fan D, Heist E K, et al.: Left ventricular lead electrical delay
predicts response to cardiac resynchronization therapy. Heart
Rhythm 2006; 3:1285-1292) while other data suggest that
specifically targeting the region of maximal mechanical delay could
improve response to CRT (see, e.g., Macias et al.; Becker M, Franke
A, Breithard O A, et al.: Impact of left ventricular lead position
on the efficacy of cardiac resynchronization therapy: a
two-dimensional strain echocardiography study. Heart 2007;
93:1197-1203; Ansalone G, Giannantoni P, Ricci R, et al.: Doppler
myocardial imaging to evaluate the effectiveness of pacing sites in
patients receiving biventricular pacing. J Am Coll Cardiol 2002;
39:489-499; Murphy R T, Sigurdsson G, Mulamalla S, et al.: Tissue
synchronization imaging and optimal left ventricular pacing site in
cardiac resynchronization therapy. Am J Cardiol 2006;
97:1615-1621).
As described herein, various exemplary techniques acquire at least
physiologic mechanical information and assess the information, for
example, to enhance guidance of LV pacing site optimization during
CRT implant. Various exemplary techniques may be applied to one or
more types of therapy (e.g., cardiac pacing therapies, ablation
therapies, sensing therapies, nerve stimulation therapies,
etc.).
SUMMARY
An exemplary method includes accessing cardiac information acquired
via a catheter located at various positions in a venous network of
a heart of a patient wherein the cardiac information comprises
position information with respect to time for one or more
electrodes of the catheter; performing a principal component
analysis on at least some of the position information; and
selecting at least one component of the principal component
analysis to represent an axis of a cardiac coordinate system.
Various other methods, devices, systems, etc., are also
disclosed.
BRIEF DESCRIPTION OF THE DRAWINGS
Features and advantages of the described implementations can be
more readily understood by reference to the following description
taken in conjunction with the accompanying drawings.
FIG. 1 is a simplified diagram illustrating an exemplary
implantable stimulation device in electrical communication with at
least three leads implanted into a patient's heart and at least one
other lead for sensing and/or delivering stimulation and/or shock
therapy. Approximate locations of the right and left phrenic nerves
are also shown. Other devices with more or fewer leads may also be
suitable for implementation of various exemplary techniques
described herein.
FIG. 2 is a functional block diagram of an exemplary implantable
stimulation device illustrating basic elements that are configured
to provide cardioversion, defibrillation, pacing stimulation and/or
other tissue stimulation. The implantable stimulation device is
further configured to sense information and administer therapy
responsive to such information.
FIG. 3 is a block diagram of an exemplary method for determining a
cardiac coordinate system and analyzing information with respect to
the cardiac coordinate system.
FIG. 4 is a diagram of an exemplary arrangement of leads and
electrodes for acquiring data and exemplary data and metrics based
on the acquired data.
FIG. 5 is a diagram of information acquired and analyzed according
to conventional echocardiography techniques.
FIG. 6 is a diagram of the heart along with various vectors that
may be used to define a cardiac coordinate system.
FIG. 7 is a diagram of a volume element model of the heart along
with a block diagram of an exemplary method to define a cardiac
coordinate system.
FIG. 8 is an anatomic map of a venous network of the heart and a
diagram of a projection technique that can define a cardiac
coordinate system.
FIG. 9 is a diagram of cross-sections of the heart along with
angles that can define a cardiac coordinate system.
FIG. 10 is a block diagram of an exemplary method and a series of
plots including a plot of electrical activity of the heart, left
ventricular circumferential motion of the heart and right
ventricular circumferential motion of the heart.
FIG. 11 is a 3-D plot of cardiac motion information and a block
diagram of an exemplary method to define a cardiac coordinate
system based on a principal component analysis (PCA).
FIG. 12 is a series of X-rays of a patient along with an overlaid
vector that represents a long axis of the heart.
FIG. 13 is a series of plots of data with respect to various
vectors.
FIG. 14 is a series of radial motion data versus time for various
conditions (i.e., intrinsic, right ventricular pacing, left
ventricular pacing and biventricular pacing).
FIG. 15 is a series of circumferential motion data versus time for
various conditions (i.e., intrinsic, right ventricular pacing, left
ventricular pacing and biventricular pacing).
FIG. 16 is a series of longitudinal motion data versus time for
various conditions (i.e., intrinsic, right ventricular pacing, left
ventricular pacing and biventricular pacing).
FIG. 17 is a series of plots for a septal motion parameter derived
in a cardiac coordinate system and an analogous echocardiography
parameter.
FIG. 18 is a plot of a dyssynchrony parameter derived in a cardiac
coordinate system and an analogous echocardiography parameter.
FIG. 19 is a block diagram of an exemplary method for determining
one or more cardiac coordinate system-based parameters and
adjusting a therapy based at least in part thereon.
FIG. 20 is a diagram of an exemplary system for acquiring
information and analyzing such information.
DETAILED DESCRIPTION
The following description includes the best mode presently
contemplated for practicing the described implementations. This
description is not to be taken in a limiting sense, but rather is
made merely for the purpose of describing the general principles of
the implementations. The scope of the described implementations
should be ascertained with reference to the issued claims. In the
description that follows, like numerals or reference designators
are typically used to reference like parts or elements
throughout.
Overview
Various exemplary techniques described herein pertain to analysis
of electrode positions in the body. For example, during an
intraoperative procedure, a clinician may maneuver an
electrode-bearing catheter to various locations in one or more
chambers or vessels of the heart and acquire position information.
As described herein, various exemplary methods include determining
a cardiac coordinate system based at least in part on acquired
position information. For example, a principal component analysis
of position information with respect to time can provide vectors
(directions) that explain variance in position. Such vectors
(directions) may also provide a basis for a cardiac coordinate
system. In various examples, position information is transformed
per a cardiac coordinate system to provide motion waveforms along a
particular direction, or directions, to provide parameters,
metrics, etc. As described herein, an exemplary method can
determine one or more parameters with respect to a cardiac
coordinate system where such parameters are analogs to conventional
parameters (e.g., echocardiography parameters). Various cardiac
coordinate system analyses may assist with treatment planning for a
cardiac pacing therapy or other cardiac-related therapy.
As described herein, an exemplary system can be configured to
assess motion of one or more leads in a patient's body by collected
information from an implanted device (e.g., via telemetry) using,
for example, a specialized localization system or an external
computing device (e.g., a device programmer). Such a collection
process may optionally occur at a standard CRT follow-up visit. An
exemplary method can include comparing information collected
post-implant to, for example, baseline information acquired
pre-implant or at the time of implant. As described herein, such
pre-implant information or time of implant information may be
archived in memory of an implantable device or elsewhere (e.g., a
database accessible by a device programmer, a localization system,
etc.). Such a method may further include determining optimal
settings for the implanted device (e.g., delays, electrode
configuration, rates, etc.).
Various exemplary methods may be implemented, for example, using a
pacing system analyzer (PSA) and a localization system or a
specialized localization system. Various examples are described
with respect to the ENSITE.RTM. NAVX.RTM. localization system (St
Jude Medical, Atrial Fibrillation Division, Minnesota); noting that
other types of localization systems may be used.
Various techniques aim to facilitate lead implantation,
particularly for leads that enter the coronary sinus to reach
distal branches thereof. For example, various techniques can allow
a clinician to view plots or maps of one or more metrics in
association with a patient's anatomy and readily decide to locate a
lead in an anatomical region with acceptable or optimal metrics for
delivery of a cardiac therapy. A typical intraoperative, acute
state process occurs iteratively (i.e., select or move, acquire,
calculate; select or move, acquire, calculate; . . . ). In this
iterative process, a clinician may note whether an anatomical
location (e.g., in a venous network) is associated with one or more
acceptable metrics or unacceptable metrics.
As described herein, various exemplary techniques can be used to
make decisions as to cardiac pacing therapy and optimization of a
cardiac pacing therapy (e.g., CRT or other pacing therapies). In a
clinical trial, acute resynchronization was shown to be a
significant factor in assessing CRT efficacy and long-term
outcome.sup.1. Various methods described herein, build on this
clinical finding by formulating specialized techniques and metrics
associated with locations for pacing, sensing or pacing and
sensing. In turn, a clinician can assess how a particular CRT
therapy or configuration thereof may be expected to perform at time
of implant or, in some instances, after implant. .sup.1 G B
Bleeker, S A Mollema, E R Holman, N Van De Veire, C Ypenburg, E
Boersma, E E van der Wall, M J Schalij, J J Bax. "Left Ventricular
Resynchronization is Mandatory for Response to Cardiac
Resynchronization Therapy: Analysis in Patients with
Echocardiographic Evidence of Left Ventricular Dyssynchrony at
Baseline". Circulation 2007; 116: 1440-1448.
An exemplary stimulation device is described followed by various
techniques for acquiring information and defining a cardiac
coordinate system. The drawings and detailed description elucidate
details of various techniques that may be used singly or in
combination during an assessment or an optimization process (e.g.,
acute or chronic).
Exemplary Stimulation Device
Various techniques described below may be implemented in connection
with a device configured or configurable for cardiac therapy, nerve
therapy or one or more other types of therapy. With reference to
FIGS. 1 and 2, an exemplary stimulation device is described, for
example, configured or configurable for delivery of one or more
types of cardiac stimulation therapy.
FIG. 1 shows an exemplary stimulation device 100 in electrical
communication with a patient's heart 102 by way of three leads (a
right atrial lead 104, a left ventricular lead 106 and a right
ventricular lead 108), suitable for delivering multi-chamber
stimulation and shock therapy. The leads 104, 106, 108 are
optionally configurable for delivery of stimulation pulses suitable
for stimulation of nerves or other tissue. In addition, in the
example of FIG. 1, the device 100 includes a fourth lead 110 having
multiple electrodes 144, 144', 144'' suitable for stimulation of
tissue and/or sensing of physiologic signals. This lead may be
positioned in and/or near a patient's heart and/or remote from the
heart.
FIG. 1 also shows approximate locations of the right and left
phrenic nerves 154, 158. The phrenic nerve is made up mostly of
motor nerve fibres for producing contractions of the diaphragm. In
addition, it provides sensory innervation for various components of
the mediastinum and pleura, as well as the upper abdomen (e.g.,
liver and gall bladder). The right phrenic nerve 154 passes over
the brachiocephalic artery, posterior to the subclavian vein, and
then crosses the root of the right lung anteriorly and then leaves
the thorax by passing through the vena cava hiatus opening in the
diaphragm at the level of T8. More specifically, with respect to
the heart, the right phrenic nerve 154 passes over the right atrium
while the left phrenic nerve 158 passes over the pericardium of the
left ventricle and pierces the diaphragm separately. While certain
therapies may call for phrenic nerve stimulation (e.g., for
treatment of sleep apnea), in general, cardiac pacing therapies
avoid phrenic nerve stimulation through judicious lead and
electrode placement, selection of electrode configurations,
adjustment of pacing parameters, etc.
Referring again to the various leads of the device 100, the right
atrial lead 104, as the name implies, is positioned in and/or
passes through a patient's right atrium. The right atrial lead 104
is configured to sense atrial cardiac signals and/or to provide
right atrial chamber stimulation therapy. As described further
below, the right atrial lead 104 may be used by the device 100 to
acquire far-field ventricular signal data. As shown in FIG. 1, the
right atrial lead 104 includes an atrial tip electrode 120, which
typically is implanted in the patient's right atrial appendage, and
an atrial ring electrode 121. The right atrial lead 104 may have
electrodes other than the tip 120 and ring 121 electrodes. Further,
the right atrial lead 104 may include electrodes suitable for
stimulation and/or sensing located on a branch.
To sense atrial cardiac signals, ventricular cardiac signals and/or
to provide chamber pacing therapy, particularly on the left side of
a patient's heart, the stimulation device 100 is coupled to the
left ventricular lead 106, which in FIG. 1 is also referred to as a
coronary sinus lead as it is designed for placement in the coronary
sinus and/or tributary veins of the coronary sinus. As shown in
FIG. 1, the coronary sinus lead 106 is configured to position at
least one distal electrode adjacent to the left ventricle and/or
additional electrode(s) adjacent to the left atrium. In a normal
heart, tributary veins of the coronary sinus include, but may not
be limited to, the great cardiac vein, the left marginal vein, the
left posterior ventricular vein, the middle cardiac vein, and the
small cardiac vein.
In the example of FIG. 1, the coronary sinus lead 106 includes a
series of electrodes 123. In particular, a series of four
electrodes are shown positioned in an anterior vein of the heart
102. Other coronary sinus leads may include a different number of
electrodes than the lead 106. As described herein, an exemplary
method selects one or more electrodes (e.g., from electrodes 123 of
the lead 106) and determines characteristics associated with
conduction and/or timing in the heart to aid in ventricular pacing
therapy and/or assessment of cardiac condition. As described in
more detail below, an illustrative method acquires information
using various electrode configurations where an electrode
configuration typically includes at least one electrode of a
coronary sinus lead or other type of left ventricular lead. Such
information may be used to determine a suitable electrode
configuration for the lead 106 (e.g., selection of one or more
electrodes 123 of the lead 106).
In the example of FIG. 1, as connected to the device 100, the
coronary sinus lead 106 is configured for acquisition of
ventricular cardiac signals (and optionally atrial signals) and to
deliver left ventricular pacing therapy using, for example, at
least one of the electrodes 123 and/or the tip electrode 122. The
lead 106 optionally allows for left atrial pacing therapy, for
example, using at least the left atrial ring electrode 124. The
lead 106 optionally allows for shocking therapy, for example, using
at least the left atrial coil electrode 126. For a complete
description of a particular coronary sinus lead, the reader is
directed to U.S. Pat. No. 5,466,254, "Coronary Sinus Lead with
Atrial Sensing Capability" (Helland), which is incorporated herein
by reference.
The stimulation device 100 is also shown in electrical
communication with the patient's heart 102 by way of an implantable
right ventricular lead 108 having, in this exemplary
implementation, a right ventricular tip electrode 128, a right
ventricular ring electrode 130, a right ventricular (RV) coil
electrode 132, and an SVC coil electrode 134. Typically, the right
ventricular lead 108 is transvenously inserted into the heart 102
to place the right ventricular tip electrode 128 in the right
ventricular apex so that the RV coil electrode 132 will be
positioned in the right ventricle and the SVC coil electrode 134
will be positioned in the superior vena cava. Accordingly, the
right ventricular lead 108, as connected to the device 100, is
capable of sensing or receiving cardiac signals, and delivering
stimulation in the form of pacing and shock therapy to the right
ventricle. An exemplary right ventricular lead may also include at
least one electrode capable of stimulating other tissue; such an
electrode may be positioned on the lead or a bifurcation or leg of
the lead. A right ventricular lead may include a series of
electrodes, such as the series 123 of the left ventricular lead
106.
FIG. 1 also shows a lead 160 as including several electrode arrays
163. In the example of FIG. 1, each electrode array 163 of the lead
160 includes a series of electrodes 162 with an associated circuit
168. Conductors 164 provide an electrical supply and return for the
circuit 168. The circuit 168 includes control logic sufficient to
electrically connect the conductors 164 to one or more of the
electrodes of the series 162. In the example of FIG. 1, the lead
160 includes a lumen 166 suitable for receipt of a guidewire to
facilitate placement of the lead 160. As described herein, any of
the leads 104, 106, 108 or 110 may include one or more electrode
array, optionally configured as the electrode array 163 of the lead
160.
FIG. 2 shows an exemplary, simplified block diagram depicting
various components of the device 100. The device 100 can be capable
of treating both fast and slow arrhythmias with stimulation
therapy, including cardioversion, defibrillation, and pacing
stimulation. While a particular multi-chamber device is shown, it
is to be appreciated and understood that this is for illustration
purposes only. Thus, the techniques, methods, etc., described below
can be implemented in connection with any suitably configured or
configurable device. Accordingly, one of skill in the art could
readily duplicate, eliminate, or disable the appropriate circuitry
in any desired combination to provide a device capable of treating
the appropriate chamber(s) or regions of a patient's heart.
Housing 200 for the device 100 is often referred to as the "can",
"case" or "case electrode", and may be programmably selected to act
as the return electrode for all "unipolar" modes. As described
below, various exemplary techniques implement unipolar sensing for
data that may include indicia of functional conduction block in
myocardial tissue. Housing 200 may further be used as a return
electrode alone or in combination with one or more of the coil
electrodes 126, 132 and 134 for shocking or other purposes. Housing
200 further includes a connector (not shown) having a plurality of
terminals 201, 202, 204, 206, 208, 212, 214, 216, 218, 221, 223
(shown schematically and, for convenience, the names of the
electrodes to which they are connected are shown next to the
terminals).
To achieve right atrial sensing, pacing and/or other tissue
sensing, stimulation, etc., the connector includes at least a right
atrial tip terminal (A.sub.R TIP) 202 adapted for connection to the
right atrial tip electrode 120. A right atrial ring terminal
(A.sub.R RING) 201 is also shown, which is adapted for connection
to the right atrial ring electrode 121. To achieve left chamber
sensing, pacing, shocking, and/or other tissue sensing,
stimulation, etc., the connector includes at least a left
ventricular tip terminal (V.sub.L TIP) 204, a left atrial ring
terminal (A.sub.L RING) 206, and a left atrial shocking terminal
(A.sub.L COIL) 208, which are adapted for connection to the left
ventricular tip electrode 122, the left atrial ring electrode 124,
and the left atrial coil electrode 126, respectively. Connection to
suitable stimulation electrodes is also possible via these and/or
other terminals (e.g., via a stimulation terminal S ELEC 221). The
terminal S ELEC 221 may optionally be used for sensing. For
example, electrodes of the lead 110 may connect to the device 100
at the terminal 221 or optionally at one or more other
terminals.
A terminal 223 allows for connection of a series of left
ventricular electrodes. For example, the series of four electrodes
123 of the lead 106 may connect to the device 100 via the terminal
223. The terminal 223 and an electrode configuration switch 226
allow for selection of one or more of the series of electrodes and
hence electrode configuration. In the example of FIG. 2, the
terminal 223 includes four branches to the switch 226 where each
branch corresponds to one of the four electrodes 123.
To support right chamber sensing, pacing, shocking, and/or other
tissue sensing, stimulation, etc., the connector further includes a
right ventricular tip terminal (V.sub.R TIP) 212, a right
ventricular ring terminal (V.sub.R RING) 214, a right ventricular
shocking terminal (RV COIL) 216, and a superior vena cava shocking
terminal (SVC COIL) 218, which are adapted for connection to the
right ventricular tip electrode 128, right ventricular ring
electrode 130, the RV coil electrode 132, and the SVC coil
electrode 134, respectively.
At the core of the stimulation device 100 is a programmable
microcontroller 220 that controls the various modes of cardiac or
other therapy. As is well known in the art, microcontroller 220
typically includes a microprocessor, or equivalent control
circuitry, designed specifically for controlling the delivery of
stimulation therapy, and may further include RAM or ROM memory,
logic and timing circuitry, state machine circuitry, and I/O
circuitry. Typically, microcontroller 220 includes the ability to
process or monitor input signals (data or information) as
controlled by a program code stored in a designated block of
memory. The type of microcontroller is not critical to the
described implementations. Rather, any suitable microcontroller 220
may be used that is suitable to carry out the functions described
herein. The use of microprocessor-based control circuits for
performing timing and data analysis functions are well known in the
art.
Representative types of control circuitry that may be used in
connection with the described embodiments can include the
microprocessor-based control system of U.S. Pat. No. 4,940,052, the
state-machine of U.S. Pat. Nos. 4,712,555 and 4,944,298, all of
which are incorporated by reference herein. For a more detailed
description of the various timing intervals used within the
stimulation device and their inter-relationship, see U.S. Pat. No.
4,788,980, also incorporated herein by reference.
FIG. 2 also shows an atrial pulse generator 222 and a ventricular
pulse generator 224 that generate pacing stimulation pulses for
delivery by the right atrial lead 104, the coronary sinus lead 106,
and/or the right ventricular lead 108 via an electrode
configuration switch 226. It is understood that in order to provide
stimulation therapy in each of the four chambers of the heart (or
to other tissue) the atrial and ventricular pulse generators, 222
and 224, may include dedicated, independent pulse generators,
multiplexed pulse generators, or shared pulse generators. The pulse
generators 222 and 224 are controlled by the microcontroller 220
via appropriate control signals 228 and 230, respectively, to
trigger or inhibit the stimulation pulses.
The microcontroller 220 further includes timing control circuitry
232 to control the timing of the stimulation pulses (e.g., pacing
rate, atrio-ventricular (AV) delay, interatrial conduction (AA)
delay, or interventricular conduction (VV) delay, etc.) as well as
to keep track of the timing of refractory periods, blanking
intervals, noise detection windows, evoked response windows, alert
intervals, marker channel timing, etc., which is well known in the
art.
The microcontroller 220 further includes an arrhythmia detector
234. The detector 234 can be utilized by the stimulation device 100
for determining desirable times to administer various therapies.
The detector 234 may be implemented in hardware as part of the
microcontroller 220, or as software/firmware instructions
programmed into the device and executed on the microcontroller 220
during certain modes of operation.
Microcontroller 220 further includes a morphology discrimination
module 236, a capture detection module 237 and an auto sensing
module 238. These modules are optionally used to implement various
exemplary recognition algorithms and/or methods presented below.
The aforementioned components may be implemented in hardware as
part of the microcontroller 220, or as software/firmware
instructions programmed into the device and executed on the
microcontroller 220 during certain modes of operation. The capture
detection module 237, as described herein, may aid in acquisition,
analysis, etc., of information relating to IEGMs and, in
particular, act to distinguish capture versus non-capture versus
fusion.
The microcontroller 220 further includes an optional position
and/or metrics module 239. The module 239 may be used for purposes
of acquiring position information, for example, in conjunction with
a device (internal or external) that may use body surface patches
or other electrodes (internal or external). The microcontroller 220
may initiate one or more algorithms of the module 239 in response
to a signal detected by various circuitry or information received
via the telemetry circuit 264. Instructions of the module 239 may
cause the device 100 to measure potentials using one or more
electrode configurations where the potentials correspond to a
potential field generated by current delivered to the body using,
for example, surface patch electrodes. Such a module may help
monitor electrode positions and cardiac mechanics in relationship
to cardiac electrical activity and may help to optimize cardiac
resynchronization therapy. The module 239 may include instructions
for vector analyses, for example, based on locally acquired or
transmitted position information. The module 239 may operate in
conjunction with various other modules and/or circuits of the
device 100 (e.g., the impedance measuring circuit 278, the switch
226, the A/D 252, etc.).
The electronic configuration switch 226 includes a plurality of
switches for connecting the desired electrodes to the appropriate
I/O circuits, thereby providing complete electrode programmability.
Accordingly, switch 226, in response to a control signal 242 from
the microcontroller 220, determines the polarity of the stimulation
pulses (e.g., unipolar, bipolar, etc.) by selectively closing the
appropriate combination of switches (not shown) as is known in the
art.
Atrial sensing circuits 244 and ventricular sensing circuits 246
may also be selectively coupled to the right atrial lead 104,
coronary sinus lead 106, and the right ventricular lead 108,
through the switch 226 for detecting the presence of cardiac
activity in each of the four chambers of the heart. Accordingly,
the atrial and ventricular sensing circuits, 244 and 246, may
include dedicated sense amplifiers, multiplexed amplifiers, or
shared amplifiers. Switch 226 determines the "sensing polarity" of
the cardiac signal by selectively closing the appropriate switches,
as is also known in the art. In this way, the clinician may program
the sensing polarity independent of the stimulation polarity. The
sensing circuits (e.g., 244 and 246) are optionally capable of
obtaining information indicative of tissue capture.
Each of the sensing circuits 244 and 246 preferably employs one or
more low power, precision amplifiers with programmable gain and/or
automatic gain control, bandpass filtering, and a threshold
detection circuit, as known in the art, to selectively sense the
cardiac signal of interest. The automatic gain control enables the
device 100 to deal effectively with the difficult problem of
sensing the low amplitude signal characteristics of atrial or
ventricular fibrillation.
The outputs of the atrial and ventricular sensing circuits 244 and
246 are connected to the microcontroller 220, which, in turn, is
able to trigger or inhibit the atrial and ventricular pulse
generators 222 and 224, respectively, in a demand fashion in
response to the absence or presence of cardiac activity in the
appropriate chambers of the heart. Furthermore, as described
herein, the microcontroller 220 is also capable of analyzing
information output from the sensing circuits 244 and 246 and/or the
data acquisition system 252 to determine or detect whether and to
what degree tissue capture has occurred and to program a pulse, or
pulses, in response to such determinations. The sensing circuits
244 and 246, in turn, receive control signals over signal lines 248
and 250 from the microcontroller 220 for purposes of controlling
the gain, threshold, polarization charge removal circuitry (not
shown), and the timing of any blocking circuitry (not shown)
coupled to the inputs of the sensing circuits, 244 and 246, as is
known in the art.
For arrhythmia detection, the device 100 may utilize the atrial and
ventricular sensing circuits, 244 and 246, to sense cardiac signals
to determine whether a rhythm is physiologic or pathologic. Of
course, other sensing circuits may be available depending on need
and/or desire. In reference to arrhythmias, as used herein,
"sensing" is reserved for the noting of an electrical signal or
obtaining data (information), and "detection" is the processing
(analysis) of these sensed signals and noting the presence of an
arrhythmia or of a precursor or other factor that may indicate a
risk of or likelihood of an imminent onset of an arrhythmia.
The exemplary detector module 234, optionally uses timing intervals
between sensed events (e.g., P-waves, R-waves, and depolarization
signals associated with fibrillation) and to perform one or more
comparisons to a predefined rate zone limit (i.e., bradycardia,
normal, low rate VT, high rate VT, and fibrillation rate zones)
and/or various other characteristics (e.g., sudden onset,
stability, physiologic sensors, and morphology, etc.) in order to
determine the type of remedial therapy (e.g., anti-arrhythmia,
etc.) that is desired or needed (e.g., bradycardia pacing,
anti-tachycardia pacing, cardioversion shocks or defibrillation
shocks, collectively referred to as "tiered therapy"). Similar
rules can be applied to the atrial channel to determine if there is
an atrial tachyarrhythmia or atrial fibrillation with appropriate
classification and intervention.
Cardiac signals are also applied to inputs of an analog-to-digital
(A/D) data acquisition system 252. The data acquisition system 252
is configured to acquire intracardiac electrogram (IEGM) signals or
other action potential signals, convert the raw analog data into a
digital signal, and store the digital signals for later processing
and/or telemetric transmission to an external device 254. The data
acquisition system 252 is coupled to the right atrial lead 104, the
coronary sinus lead 106, the right ventricular lead 108 and/or
another lead (e.g., the lead 110) through the switch 226 to sample
cardiac signals or other signals across any pair or other number of
desired electrodes. A control signal 256 from the microcontroller
220 may instruct the A/D 252 to operate in a particular mode (e.g.,
resolution, amplification, etc.).
Various exemplary mechanisms for signal acquisition are described
herein that optionally include use of one or more analog-to-digital
converter. Various exemplary mechanisms allow for adjustment of one
or more parameter associated with signal acquisition.
The microcontroller 220 is further coupled to a memory 260 by a
suitable data/address bus 262, wherein the programmable operating
parameters used by the microcontroller 220 are stored and modified,
as required, in order to customize the operation of the stimulation
device 100 to suit the needs of a particular patient. Such
operating parameters define, for example, pacing pulse amplitude,
pulse duration, electrode polarity, rate, sensitivity, automatic
features, arrhythmia detection criteria, and the amplitude,
waveshape, number of pulses, and vector of each shocking pulse to
be delivered to the patient's heart 102 within each respective tier
of therapy. One feature of the described embodiments is the ability
to sense and store a relatively large amount of data (e.g., from
the data acquisition system 252), which data may then be used for
subsequent analysis to guide the programming and operation of the
device 100.
Advantageously, the operating parameters of the implantable device
100 may be non-invasively programmed into the memory 260 through a
telemetry circuit 264 in telemetric communication via communication
link 266 with the external device 254, such as a programmer,
transtelephonic transceiver, or a diagnostic system analyzer. The
microcontroller 220 activates the telemetry circuit 264 with a
control signal 268. The telemetry circuit 264 advantageously allows
intracardiac electrograms (IEGM) and other information (e.g.,
status information relating to the operation of the device 100,
etc., as contained in the microcontroller 220 or memory 260) to be
sent to the external device 254 through an established
communication link 266.
The stimulation device 100 can further include one or more
physiologic sensors 270. For example, the device 100 may include a
"rate-responsive" sensor that may provide, for example, information
to aid in adjustment of pacing stimulation rate according to the
exercise state of the patient. However, the one or more
physiological sensors 270 may further be used to detect changes in
cardiac output (see, e.g., U.S. Pat. No. 6,314,323, entitled "Heart
stimulator determining cardiac output, by measuring the systolic
pressure, for controlling the stimulation", to Ekwall, issued Nov.
6, 2001, which discusses a pressure sensor adapted to sense
pressure in a right ventricle and to generate an electrical
pressure signal corresponding to the sensed pressure, an integrator
supplied with the pressure signal which integrates the pressure
signal between a start time and a stop time to produce an
integration result that corresponds to cardiac output), changes in
the physiological condition of the heart, or diurnal changes in
activity (e.g., detecting sleep and wake states). Accordingly, the
microcontroller 220 responds by adjusting the various pacing
parameters (such as rate, AV Delay, VV Delay, etc.) at which the
atrial and ventricular pulse generators, 222 and 224, generate
stimulation pulses.
While shown as being included within the stimulation device 100, it
is to be understood that one or more of the physiologic sensors 270
may also be external to the stimulation device 100, yet still be
implanted within or carried by the patient. Examples of physiologic
sensors that may be implemented in device 100 include known sensors
that, for example, sense respiration rate, oxygen concentration of
blood, pH of blood, CO.sub.2 concentration of blood, ventricular
gradient, cardiac output, preload, afterload, contractility, and so
forth. Another sensor that may be used is one that detects activity
variance, wherein an activity sensor is monitored diurnally to
detect the low variance in the measurement corresponding to the
sleep state. For a complete description of the activity variance
sensor, the reader is directed to U.S. Pat. No. 5,476,483 which is
hereby incorporated by reference.
The one or more physiologic sensors 270 optionally include sensors
for detecting movement and minute ventilation in the patient.
Signals generated by a position sensor, a MV sensor, etc., may be
passed to the microcontroller 220 for analysis in determining
whether to adjust the pacing rate, etc. The microcontroller 220 may
monitor the signals for indications of the patient's position and
activity status, such as whether the patient is climbing upstairs
or descending downstairs or whether the patient is sitting up after
lying down.
The stimulation device 100 additionally includes a battery 276 that
provides operating power to all of the circuits shown in FIG. 2.
For the stimulation device 100, which employs shocking therapy, the
battery 276 is capable of operating at low current drains for long
periods of time (e.g., preferably less than 10 .mu.A), and is
capable of providing high-current pulses (for capacitor charging)
when the patient requires a shock pulse (e.g., preferably, in
excess of 2 A, at voltages above 200 V, for periods of 10 seconds
or more). The battery 276 also desirably has a predictable
discharge characteristic so that elective replacement time can be
detected.
The stimulation device 100 can further include magnet detection
circuitry (not shown), coupled to the microcontroller 220, to
detect when a magnet is placed over the stimulation device 100. A
magnet may be used by a clinician to perform various test functions
of the stimulation device 100 and/or to signal the microcontroller
220 that the external programmer 254 is in place to receive or
transmit data to the microcontroller 220 through the telemetry
circuits 264.
The stimulation device 100 further includes an impedance measuring
circuit 278 that is enabled by the microcontroller 220 via a
control signal 280. The known uses for an impedance measuring
circuit 278 include, but are not limited to, lead impedance
surveillance during the acute and chronic phases for proper lead
positioning or dislodgement; detecting operable electrodes and
automatically switching to an operable pair if dislodgement occurs;
measuring respiration or minute ventilation; measuring thoracic
impedance for determining shock thresholds; detecting when the
device has been implanted; measuring stroke volume; and detecting
the opening of heart valves, etc. The impedance measuring circuit
278 is advantageously coupled to the switch 226 so that any desired
electrode may be used.
In the case where the stimulation device 100 is intended to operate
as an implantable cardioverter/defibrillator (ICD) device, it
detects the occurrence of an arrhythmia, and automatically applies
an appropriate therapy to the heart aimed at terminating the
detected arrhythmia. To this end, the microcontroller 220 further
controls a shocking circuit 282 by way of a control signal 284. The
shocking circuit 282 generates shocking pulses of low (e.g., up to
0.5 J), moderate (e.g., 0.5 J to 10 J), or high energy (e.g., 11 J
to 40 J), as controlled by the microcontroller 220. Such shocking
pulses are applied to the patient's heart 102 through at least two
shocking electrodes, and as shown in this embodiment, selected from
the left atrial coil electrode 126, the RV coil electrode 132,
and/or the SVC coil electrode 134. As noted above, the housing 200
may act as an active electrode in combination with the RV electrode
132, or as part of a split electrical vector using the SVC coil
electrode 134 or the left atrial coil electrode 126 (i.e., using
the RV electrode as a common electrode).
Cardioversion level shocks are generally considered to be of low to
moderate energy level (so as to minimize pain felt by the patient),
and/or synchronized with an R-wave and/or pertaining to the
treatment of tachycardia. Defibrillation shocks are generally of
moderate to high energy level (e.g., corresponding to thresholds in
the range of approximately 5 J to 40 J), delivered asynchronously
(since R-waves may be too disorganized), and pertaining exclusively
to the treatment of fibrillation. Accordingly, the microcontroller
220 is capable of controlling the synchronous or asynchronous
delivery of the shocking pulses.
As already mentioned, the implantable device 100 includes impedance
measurement circuitry 278. Such a circuit may measure impedance or
electrical resistance through use of various techniques. For
example, the device 100 may deliver a low voltage (e.g., about 10
mV to about 20 mV) of alternating current between the RV tip
electrode 128 and the case electrode 200. During delivery of this
energy, the device 100 may measure resistance between these two
electrodes where the resistance depends on any of a variety of
factors. For example, the resistance may vary inversely with
respect to volume of blood along the path.
In another example, resistance measurement occurs through use of a
four terminal or electrode technique. For example, the exemplary
device 100 may deliver an alternating current between one of the RV
tip electrode 128 and the case electrode 200. During delivery, the
device 100 may measure a potential between the RA ring electrode
121 and the RV ring electrode 130 where the potential is
proportional to the resistance between the selected potential
measurement electrodes.
With respect to two terminal or electrode techniques, where two
electrodes are used to introduce current and the same two
electrodes are used to measure potential, parasitic
electrode-electrolyte impedances can introduce noise, especially at
low current frequencies; thus, a greater number of terminals or
electrodes may be used. For example, aforementioned four electrode
techniques, where one electrode pair introduces current and another
electrode pair measures potential, can cancel noise due to
electrode-electrolyte interface impedance. Alternatively, where
suitable or desirable, a two terminal or electrode technique may
use larger electrode areas (e.g., even exceeding about 1 cm.sup.2)
and/or higher current frequencies (e.g., above about 10 kHz) to
reduce noise.
FIG. 3 shows an exemplary method 300 for transforming acquired
information and for analyzing the transformed information. The
method 300 is shown with respect to an intraoperative setting 304
and a clinical or other setting 308. The intraoperative setting 304
includes a system for acquiring information, for example, by
placing a catheter in a patient's body. The system may be
configured to transmit acquired information to a data storage
(e.g., database), for example, via a network. The clinical (or
other) setting 308 includes a computing device configured to at
least analyze information and optionally transform information. The
system of the clinical setting 308 may perform such actions on
information acquired by a system in the intraoperative setting 304,
for example, where such information is stored in a database, a
removable storage medium, or communicated to the system of the
clinical setting 308.
In the example of FIG. 3, the method 300 includes an acquisition
block 310 that acquires information with respect to a naive
coordinate system (e.g., a Cartesian coordinate system X, Y, Z).
For example, a plot 315 shows data in a naive coordinate system
where the data includes right atrial (RA) electrode motion data,
coronary sinus (CS) electrode motion data and right ventricular
(RV) electrode motion data. In a determination block 320, the
method 300 determines a cardiac coordinate system (i.e., non-naive
coordinate system) based at least in part on the acquired
information. Examples of some techniques include principal
component analysis (PCA), vector rotation (see, e.g., FIG. 6),
model tagging (see, e.g., FIG. 7), coronary sinus projection (see,
e.g., FIG. 8) and vector angle (see, e.g., FIG. 9). A plot 325
shows the acquired data in a cardiac coordinate system (CCS) (e.g.,
a cylindrical coordinate system Z', R, C). In this example, the
axis Z' is aligned with the direction of largest variance of the
acquired data. In an analysis block 330, the method 300 analyzes
the information with respect to the CCS. Plots 335 show position
versus time data along the Z' axis, the R axis and the
circumferential (azimuthal) angle C with respect to time for
intrinsic activation of the heart and for biventricular paced
activation of the heart (CRT). As described herein, analysis of
data in a patient specific CCS can provide insight into cardiac
mechanics and assist placement of one or more electrodes for
delivery of a cardiac therapy (e.g., stimulation, sensing, etc.).
Further, such an analysis may help to set or adjust one or more
therapy parameters (e.g., stimulation parameters such as timing,
energy, duration, polarity, delays, etc.). Yet further, such an
analysis may help diagnose one or more cardiac conditions (e.g.,
based on trends, comparisons to other patient data, types of
motion, lack of motion, etc.).
As described herein, various exemplary methods may rely on
principal component analysis (PCA) to define a cardiac coordinate
system (CCS) based on data acquired with respect to a naive
coordinate system (NCS).
PCA may be viewed as a variable reduction procedure, particularly
useful for analyzing data obtained for a number of variables
(possibly a large number of variables) where some redundancy is
believed to exist amongst those variables. In this case, redundancy
means that some of the variables are correlated with one another,
possibly because they are measuring the same construct. Due to
redundancy, it should be possible to reduce the observed variables
into a smaller number of principal components (sometimes referred
to as "artificial" variables) that can account for most of the
variance in the observed variables. As described herein, PCA is
used to determine a cardiac coordinate system that accounts for
variance in cardiac motion, for example, to find a principal
component that describes most of the directional motion of the
heart. For example, an exemplary PCA analysis may provide insight
as to cardiac motion related to body position, drug administration,
intrinsic activation, atrial pacing, right ventricular pacing, left
ventricular pacing, biventricular pacing, other multi-chamber
pacing, etc.
In PCA, the first component extracted accounts for a maximal amount
of total variance in the observed variables; in general, the first
component will be correlated with at least some of the observed
variables and it may be correlated with many. The second component
extracted accounts for a maximal amount of variance in the data set
that was not accounted for by the first component, which, in
general, means that the second component will be correlated with
some of the observed variables that did not display strong
correlations with first component. Also, in general terms, the
second component will be uncorrelated with the first component
(i.e., the correlation between the first and second components
should be zero). Other remaining components extracted via PCA
display the same two characteristics as the second component: each
component accounts for a maximal amount of variance in the observed
variables that was not accounted for by the preceding components,
and is uncorrelated with all of the preceding components. As each
additional component accounts for progressively smaller and smaller
amounts of variance, in general, the first few components are
usually relied on for interpreting the data.
In general, PCA makes no assumption about an underlying causal
model. However, as described herein, cardiac mechanics may be
considered as being more readily represented in a cylindrical or
coordinate system other than a Cartesian coordinate system. In
various examples, a naive coordinate system (NCS) is Cartesian and
a cardiac coordinate system (CCS) is cylindrical. As described
herein, one or more other types of coordinate systems suitable for
modeling cardiac mechanics may be used as a CCS (e.g., spherical,
oblate spherical, prolate spherical, etc.). For example, the heart
may be modeled as a spheroid or a chamber of the heart may be
modeled as a spheroid. As the left ventricle provides significant
pumping action, an analysis may focus on the left ventricle
modeled, for example, as a cylinder or a prolate spheroid. In such
an example, a prolate spheroid model may be fit to acquired
information and optionally a coordinate system extracted from the
fit prolate spheroid model (e.g., to provide a non-naive coordinate
system). A fitting process may include providing one or more
non-linear equations with associated parameters to define a prolate
spheroid or a portion thereof and, for example, applying a
least-squares technique to minimize error between data and a value
of an equation (or values of equations).
With respect to an image-based localization technique with a naive
3-D coordinate system (X, Y, Z), consider measurements of electrode
motion being recorded in three naive planes XY, XZ and YZ
associated with, for example, a fluoroscopic technique (e.g.,
projections from three observation points). For an exemplary PCA
scheme, each electrode may be viewed as moving in the dimensions
defined by each of the three planes (i.e., six measurement
dimensions, two for each plane). In such a scheme, every
position-time sample for an electrode may be viewed as a vector
(e.g., with respect to a root or null position) in a space spanned
by some orthonormal basis. As described herein, the underlying
orthonormal basis can be determined using an exemplary PCA scheme.
Specifically, such a PCA scheme can re-express each of the original
samples through a linear combination of orthonormal basis vectors
(e.g., to define a CCS).
As an example, let A be an original data set, where each column is
a single sample (or moment in time) of the data set. In an
electrode example, A is an m.times.n matrix where m=M (number of
dimensions) and n=N (total number of samples). Let B be another
m.times.n matrix related by a linear transformation P. A is the
original recorded data set and B is a re-representation of that
data set: PA=B where P is a matrix that transforms A into B (e.g.,
geometrically, P is a typically a rotation and a stretch that
transforms A into B). The rows of P, {p.sub.1, . . . , p.sub.m},
are a set of new basis vectors for expressing the columns of A. In
other words, the rows of P are a new set of basis vectors for
representing columns of A.
With respect to a cardiac coordinate system (CCS), directions with
largest variances in a measurement vector space are assumed to
contain dynamics of interest. Further, the direction with the
largest variance may be presumed to have the highest
signal-to-noise ratio (SNR). In contrast, a coordinate system of
the naive basis (e.g., X, Y, Z coordinate system) is unlikely to
have any of its axes correspond to the direction of largest
variance. As to this point, an exemplary PCA approach that defines
one or more axes of a cardiac coordinate system can optionally be
used to alleviate some uncertainty for placement of patches of a
localization system. For example, once an orthonormal basis is
found for a particular patient (or more generally for a population
of patients), a clinician may place patches, fluoroscopic
equipment, etc., in a manner to more closely align a naive basis of
a localization system (e.g., image-based, electrical signal-based,
etc.) to an underlying physiologic orthonormal basis that accounts
for cardiac motion.
Referring to the matrices A and B, an exemplary PCA scheme can
include selecting a normalized direction in m-dimensional space
along which variance in A is maximized and saving this vector as
p.sub.1. Next, the scheme can include finding another direction
along which variance is maximized, however, because of the
orthonormality condition, a search can be restricted to all
directions perpendicular to all previous selected directions. The
resulting vector may then be saved as P.sub.i. The process as to
p.sub.i can be repeating until m vectors are selected. Accordingly,
the resulting ordered set of p's are the principal components. Such
a process is amenable to solution by linear algebra as there exist
decompositions that can provide efficient, explicit algebraic
solutions (e.g., based on eigenvector decomposition or singular
value decomposition).
A particular approach may be summarized as finding some orthonormal
matrix P where B=PA such that the covariance matrix
Cov.sub.B.ident.(n-1).sup.-1 BB.sup.T is diagonalized and the rows
of P are the principal components of A. Other types of component
analysis include independent component analysis (ICA). Further,
techniques that account for known behavior (e.g., known mechanics
or theoretical mechanics) may be relied on, for example, to
transform sample data prior to a component analysis. For example,
sample data may be transformed from a naive Cartesian coordinate
system to what may be considered a less "naive" cylindrical
coordinate system where rotational motion is known to exist.
Analyses involving principal curves or manifolds may help to
explain natural geometry (e.g., to extend geometric interpretation
of PCA).
As described herein, an intraoperative exploration procedure to
acquire information relies on acquisition equipment. For example,
an exploration procedure may rely on a localization system such as
the ENSITE.RTM. NAVX.RTM. system or other system with appropriate
localization features. The ENSITE.RTM. NAVX.RTM. localization
system includes patch electrodes for placement on a patient's body
that can establish a multidimensional localization field (e.g., by
delivery of current using patch electrodes). Given a localization
field, the ENSITE.RTM. NAVX.RTM. system can use an electrode
positioned in the body of the patient to measure electrical
potential and, in turn, to determine a position for the electrode.
Where an electrode is positioned in a cardiac space (e.g., cardiac
surface, cardiac chamber, cardiac vein, etc.), the ENSITE.RTM.
NAVX.RTM. system can acquire electrical potential with respect to
time to generate a mechanical waveform indicative of cardiac
motion. Such a waveform may be analyzed (or acquired) with respect
to electrical information, for example, to determine position,
displacement, velocity, acceleration, etc., of an electrode in
response to cardiac motion (e.g., peak systolic, peak diastolic,
etc.).
Acquired information can include electrical information such as
electrical activation times and cardiac potentials and mechanical
information such as mechanical activation times, motion waveforms,
path length, velocity, etc. Such information may be acquired or
determined with respect to anatomic features such as a venous
network of the heart. The primary venous network of the heart
includes the coronary sinus, which empties into the right atrium
via the coronary sinus ostium. The coronary sinus network drains
about 95% of the venous blood of the myocardium (the remaining 5%
of myocardial venous flow drains through the thebesian
vessels).
The coronary sinus has various tributary veins including the small,
middle, great and oblique cardiac veins, the left marginal vein and
the left posterior ventricular vein. The great cardiac vein is
normally the longest venous vessel of the heart. The great and the
middle cardiac veins normally merge at the apex of the heart,
forming together with the coronary sinus, a fairly complete venous
ring around the left ventricle. Consequently, these tributaries of
the coronary sinus are often considered as candidates when deciding
where to place a lead for electrical activation of the left
ventricle.
In general, the extent of exploration of a venous network depends
on catheter characteristics. For example, a catheter with a large
cross-sectional dimension or high rigidity may be suited for
navigation of the coronary sinus but only partial navigation of one
or more tributaries of the coronary sinus. In contrast, leads
typically configured for stimulation therapies have small
cross-section dimension and are quite flexible to allow for deep
access to the heart's venous network.
In some instances, a catheter may be configured to acquire data
such as temperature or flow (e.g., thermodilution). In such
instances, flow, temperature or other data may be acquired. While
blood from the coronary sinus drains to the heart, flow to the
coronary sinus still effectively transports heat energy to aid in
cooling the heart. Various studies demonstrate relationships
between flow in the coronary sinus or tributaries thereof with
conditions such as ischemia. Such information may help localize
ischemia and, as described herein, improve selection of an
appropriate venous branch for locating one or more lead-based
electrodes, sensors or other therapeutic equipment. Where such
information is localized using a localization system, the
information may be mapped or otherwise presented or analyzed in
conjunction with localized electrical information, mechanical
information, etc. Accordingly, a rich understanding of a patient's
venous network, particularly the coronary sinus, may be
attained.
Referring again to FIG. 3, an analysis of information with respect
to a cardiac coordinate system may be used, optionally in
combination with other information, to determine one or more
locations for placement of a lead, placement of a sensor, placement
of ablation therapy equipment, placement of nerve therapy
equipment, etc.
As mentioned, a localization system such as the ENSITE.RTM.
NAVX.RTM. system may be used to acquire position information.
Further, a localization system may include analysis features that
allow for essentially real-time display of information as such
information is acquired and optionally analyzed during an
exploration of the venous network of a patient. As described
herein, real-time information may be mapped in conjunction with
previously acquired information (e.g., prior intraoperative
exploration or image information from CT, MR or ultrasound
studies).
During an information acquisition procedure, a clinician may
explore a venous network while delivering electrical energy to
stimulate the heart, for example, as indicated in the plots 335 of
FIG. 3 for intrinsic and CRT. Further, delivery parameters may be
varied to determine whether a location in a selected tributary of
the coronary sinus is suitable for a therapy. For example, with
respect to a stimulation therapy, a clinician may vary polarity,
energy level, pulse shape, pulse duration, etc., during a procedure
while acquiring position information (e.g., electrical potentials
measured in a localization field). Where a procedure includes
inserting multiple electrode-bearing leads, various electrodes on
those leads may be used to acquire position information, for
example, to understand cardiac mechanics responsive to the
delivered stimulation energy. Further, such electrodes may acquire
potentials associated with cardiac activity. Accordingly, an
analysis process may generate dynamic diagnostics of mechanical and
electrical information and render diagnostic information to a
display in near real-time to allow a clinician to expeditiously
explore a tributary to the coronary sinus and select an optimal
location for therapeutic equipment (e.g., an electrode, a sensor,
an ablation device, etc.).
In a post-implant or chronic phase, a follow-up procedure may take
place in a clinical setting to acquire data and verify or optimize
parameters associated with a therapy that relies on an implantable
device. Depending on the capabilities of the device and clinical
equipment, various types of information may be acquired. As
explained with respect to the device 100 of FIGS. 1 and 2, a
typical cardiac stimulation device is configured for telemetric
communication with an external device, sometimes referred to as a
device programmer. The device may transmit acquired information to
an external device and respond to instructions received from an
external device. An implanted device may transmit IEGMs (electrical
information) as well as other information (e.g., depending of
device capabilities). For example, with respect to mechanical
information, the implanted device may include an accelerometer,
impedance circuitry, etc., which may be used to acquire information
related to cardiac mechanics. An implanted device or an external
device may assess cardiac performance based on acquired
information. In turn, one or more therapy parameters may be
verified or optimized. Further, depending on the clinical setting,
echocardiography, CT or other equipment may be available to acquire
information to aid in an assessment of cardiac performance,
implanted device performance, etc. Yet further, an external system
may be available to generate a localization field where implanted
electrodes can measure electrical potential in the localization
field. Where such a system is available, a follow-up procedure may
include verification or optimization based on such position
information (e.g., akin to the aforementioned ENSITE.RTM. NAVX.RTM.
system analyses).
As described herein, where an exemplary coronary sinus analysis
technique is used to enhance a cardiac stimulation therapy, one may
expect values for time from RV pace to electrical activation of the
LV to become more homogeneous after commencement of CRT therapy.
Further, an analysis of information acquired from an exploration of
a venous network may provide an indication of potential CRT
efficacy or response and optionally, after delivery of CRT, such an
analysis may help to determine whether a patient is a CRT
responder. In addition, where electrode position can be determined
post-implant, lead motion data may be compared to baseline
measurements taken at the time of coronary sinus mapping or CRT
implant (or both).
After implantation and between follow-up visits, a device-based
acquisition process may acquire various types of information
including electrical information and optionally mechanical
information. An implanted device may be configured to acquire
information and to verify or optimize one or more parameters based
on such information. For example, the QUICKOPT.RTM. algorithm (St.
Jude Medical, Inc.) can allow for device-based verification or
optimization of AV and VV delays based on acquired electrical
information.
As described herein, data acquired during an intraoperative
procedure and data acquired post-implant (e.g., chronic data), or
analyses based on such data, may be stored in a database. Where a
database stores data or analyses for many patients, it may be
relied on during any of the various stages of therapy planning and
delivery. Information may be used to track progress of a patient
over time. Further, a trend for a patient or implanted device may
be compared to trends for other patients or other implanted
devices. As to storage, information may be stored in an implantable
device, a programmer configured with storage, a networked storage
device, a removable storage device (e.g., a memory card), etc.
Where an implantable device stores data, the data may be relied on
in making decisions as to delivery of therapy (e.g., setting one or
more therapy parameters, trend analysis, etc.).
FIG. 4 shows an arrangement and method 400 that may rely in part on
a commercially available system marketed as ENSITE.RTM. NAVX.RTM.
navigation and visualization system (see also LOCALISA.RTM. system,
Medtronic, Inc., Minnesota). The ENSITE.RTM. NAVX.RTM. system is a
computerized storage and display system for use in
electrophysiology studies of the human heart. The system consists
of a console workstation, patient interface unit, and an
electrophysiology mapping catheter and/or surface electrode kit. By
visualizing the global activation pattern seen on color-coded
isopotential maps in the system, in conjunction with the
reconstructed electrograms, an electrophysiologist can identify the
source of an arrhythmia and can navigate to a defined area for
therapy. The ENSITE.RTM. system is also useful in treating patients
with simpler arrhythmias by providing non-fluoroscopic navigation
and visualization of conventional electrophysiology (EP)
catheters.
As shown in FIG. 4, electrodes 432, 432', which may be part of a
standard EP catheter 430 (or lead), sense electrical potential
associated with current signals transmitted between three pairs of
surface electrode patches 422, 422' (X-axis), 424, 424' (Y-axis)
and 426, 426' (Z-axis). An addition electrode patch 428 (sometimes
referred to as a "belly" patch) is available for reference,
grounding or other function. The ENSITE.RTM. NAVX.RTM. system can
also collect electrical data from a catheter and can plot a cardiac
electrogram from a particular location (e.g., cardiac vein 103 of
heart 102). Information acquired may be displayed as a 3-D
isopotential map and as virtual electrograms. Repositioning of the
catheter allows for plotting of cardiac electrograms from other
locations. Multiple catheters may be used as well. A cardiac
electrogram or electrocardiogram (ECG) of normal heart activity
(e.g., polarization, depolarization, etc.) typically shows atrial
depolarization as a "P wave", ventricular depolarization as an "R
wave", or QRS complex, and repolarization as a "T wave". The
ENSITE.RTM. NAVX.RTM. system may use electrical information to
track or navigate movement and construct three-dimensional (3-D)
models of a chamber of the heart.
A clinician can use the ENSITE.RTM. NAVX.RTM. system to create a
3-D model of a chamber in the heart for purposes of treating
arrhythmia (e.g., treatment via tissue ablation). To create the 3-D
model, the clinician applies surface patches to the body (e.g., to
define a naive coordinate system). The ENSITE.RTM. NAVX.RTM. system
transmits an electrical signal between the patches and the system
then senses the electrical signal using one or more catheters
positioned in the body. The clinician may sweep a catheter with
electrodes across a chamber of the heart to outline structure.
Signals acquired during the sweep, associated with various
positions, can then be used to generate a 3-D model. A display can
display a diagram of heart morphology, which, in turn, may help
guide an ablation catheter to a point for tissue ablation.
With respect to the foregoing discussion of current delivery and
potential measurement, per a method 440, a system (e.g., such as
the ENSITE.RTM. NAVX.RTM. system) delivers low level separable
currents from the three substantially orthogonal electrode pairs
(422, 422', 424, 424', 426, 426') positioned on the body surface
(delivery block 442). The specific position of a catheter (or lead)
electrode within a chamber of the heart can then be established
based on three resulting potentials measured between the recording
electrode with respect to a reference electrode, as seen over the
distance from each patch set to the recording electrode
(measurement block 444). Sequential positioning of a catheter (or
lead) at multiple sites along the endocardial surface of a specific
chamber can establish that chamber's geometry, i.e., position
mapping (position determination block 446). Where the catheter (or
lead) 430 moves (e.g., due to cardiac mechanics), the method 440
may also measure motion.
In addition to mapping at specific points, the ENSITE.RTM.
NAVX.RTM. system provides for interpolation (e.g., for mapping a
smooth surface) onto which activation voltages and times can be
registered. Around 50 points are required to establish a surface
geometry and activation of a chamber at an appropriate resolution.
The ENSITE.RTM. NAVX.RTM. system also permits the simultaneous
display of multiple catheter electrode sites, and also reflects
real-time motion of both ablation catheters and those positioned
elsewhere in the heart.
The ENSITE.RTM. NAVX.RTM. system relies on catheters for temporary
placement in the body. Various exemplary techniques described
herein optionally use one or more electrodes for chronic
implantation. Such electrodes may be associated with a lead, an
implantable device, or other chronically implantable component.
With respect to motion (e.g., change in position with respect to
time), the exemplary system and method 400 may track motion of an
electrode in one or more dimensions. For example, a plot 450 of
motion versus time for three dimensions (X, Y, Z) corresponds to
motion of one or more electrodes of the catheter (or lead) 430
positioned in a vessel 103 of the heart 102 where the catheter (or
lead) 430 includes the one or more electrodes 432, 432'. Motion of
the catheter (or lead) 430 may exhibit hysteresis over a cardiac
cycle. For example, a systolic path may differ from a diastolic
path. An exemplary method may analyze hysteresis for any of a
variety of purposes including assessing stability of an electrode
of a catheter (or lead), assessing stability of a catheter (or
lead), selection of a stimulation site, selection of a sensing
site, diagnosis of cardiac condition, etc.
The exemplary method 440, as mentioned, includes the delivery block
442 for delivery of current, the measurement block 444 to measure
potential in a field defined by the delivered current and the
determination block 446 to determine position or motion based at
least in part on the measured potential. According to such a
method, position or motion during systole and/or diastole may be
associated with electrical information or other information (e.g.,
biosensor, loading of a catheter or lead, intrinsic/paced
activation, etc.). Alone, or in combination with other information,
the position or motion information may be used for various
assessments (e.g., stability assessments), selection of optimal
stimulation site(s), determination of hemodynamic surrogates (e.g.,
surrogates to stroke volume, contractility, etc.), optimization of
CRT, placement of leads, determination of pacing parameters (AV
delay, VV delay, etc.), etc.
The system 400 may use one or more features of the aforementioned
ENSITE.RTM. NAVX.RTM. system. For example, one or more pairs of
electrodes (422, 422', 424, 424', 426, 426' and optionally 428) may
be used to define one or more dimensions by delivering an
electrical signal or signals to a body and/or by sensing an
electrical signal or signals. Such electrodes (e.g., patch
electrodes) may be used in conjunction with one or more electrodes
positioned in the body (e.g., the electrodes 432, 432').
The exemplary system 400 may be used to track position or motion of
one or more electrodes due to systolic function, diastolic
function, respiratory function, etc. Electrodes may be positioned
along the endocardium and/or epicardium during a scouting or
mapping process for use in conjunction with electrical information.
Such information may also be used alone, or in conjunction with
other information (e.g., electrical information), for assessing
stability of an electrode or electrodes for use in delivering a
therapy or for identifying the optimal location of an electrode or
electrodes for use in delivering a therapy. For example, a location
may be selected for optimal stability, for optimal stimulation, for
optimal sensing, or for other purposes.
With respect to stimulation, stimulation may be delivered to
control cardiac mechanics (e.g., contraction of a chamber of the
heart) or nerve action and position or motion information may be
acquired where such information is associated with the controlled
cardiac mechanics or controlled nerve action; noting that other
types of interventions may also be applied (e.g., body position,
drugs, etc.). An exemplary selection process may identify the best
stimulation site based on factors such as electrical activity,
electromechanical delay, extent of motion, synchrony of motion
where motion may be classified as motion due to systolic function
or motion due to diastolic function. In general, cardiac motion
information corresponds to motion of an electrode or electrodes
(e.g., endocardial electrodes, epicardial electrodes, etc.) and may
be related to motion of the heart or other physiology. In instances
pertaining to nerve stimulation therapy, motion may be, for
example, respiratory motion (e.g., diaphragm motion due to
stimulation of a phrenic nerve).
As described with respect to FIG. 4, a localization system can
acquire position information for one or more electrodes on a lead
or catheter. The ENSITE.RTM. NAVX.RTM. system can operate at a
sampling frequency around 100 Hz (10 ms), which, for a cardiac
rhythm of 60 bpm, allows for 100 samples per electrode per cardiac
cycle. In various examples, sampling may be gated to occur over
only a portion of a cardiac cycle. Gating may rely on fiducial
markers such as peaks, gradients, crossings, etc., in an
electrogram of heart activity. Other techniques for gating can
include accelerometer techniques, impedance techniques, pressure
techniques, flow techniques, etc. For example, an accelerometer
signal slope above a threshold value (e.g., due to cardiac
contraction or relaxation) can be used to commence acquisition of
information or to terminate acquisition of information during a
cardiac cycle. Such a technique may be repeated over multiple
cardiac cycles with or without application of electrical stimuli,
medication, body position changes, etc.
As described herein, for one or more electrodes, a localization
system can provide four-dimensional information (e.g., X, Y, Z and
time). The four-dimensional information describes a
three-dimensional trajectory in space that can be analyzed or
displayed in part, in whole or at one or more key points in time.
As mentioned, various other types of information may be used to
gate acquisition or to delineate points or segments of a
trajectory. For example, information provided by a surface ECG, an
intracardiac EGM (IEGM), or other biosignal can delineate a point
or event such as QRS onset or pacing pulse or a segment (e.g., QRS
complex, QT interval, etc.).
Where an electrode is position in a vessel of the heart such as a
vein (e.g., CS or a tributary thereof), the trajectory of the
electrode will follow cardiac motion of nearby myocardium. For
example, a CS lead electrode will trace the path traversed by
epicardium adjacent the CS or adjacent the particular CS tributary.
If the lead position is stable in a branch, the trajectory for
consecutive beats will typically remain within a bounded spatial
volume; however, if the lead dislodges grossly, a shift in the CS
lead electrode's position will be apparent in a display or analysis
of the acquired information.
In various instances, depending on placement of electrodes that
generate a localization field, respiration may affect accuracy of
position data. For example, referring to FIG. 4, as a patient
breathes, the torso changes shape, which can alter the alignment of
the electrodes 422, 422', 424, 424', 426, 426' and 428. Further, as
respiration introduces air into the body, dielectric properties of
media between electrodes of a directional pair may change. To
account for the affects of respiration, an exemplary data
acquisition technique may include an algorithm that compensates for
respiratory motion. Alternatively, compensation of filtering may be
performed after data acquisition, for example, using one or more
algorithms that identify frequencies in data that are likely
related to respiration and adjust the data (e.g., filter or
normalize) to compensate for respiration. In other instances,
respiration gating may be used during data acquisition, for
example, akin to techniques used during acquisition of nuclear
magnetic resonance data (e.g., NMR or MRI data). For example, beats
to be included in a stability index metric may be gated to a
particular portion of the respiratory cycle.
As described herein, an exemplary method that relies on a component
analysis (e.g., PCA) may find one or more components associated
with respiration. For example, if a catheter is placed in at a
location (e.g., in a vein) that moves with respect to respiratory
movement and minimally with respect to cardiac motion, PCA may
determine a direction (e.g., an axis) that accounts for variance
associated with respiratory movement. As described herein, motion
detected along a respiratory direction may optionally be used for
gating (e.g., defining a window) or one or more other purposes.
The ENSITE.RTM. NAVX.RTM. system includes a so-called "RespComp"
algorithm that uses a combination of impedance between various
pairs of patches, which create the localization field, as a measure
of respiratory motion. In yet another alternative, motion of
electrodes that are known to be stable can be used to ascertain
respiratory motion. For example, position data with respect to time
may have low frequency content (approximately 0.1 Hz to
approximately 0.5 Hz) that can be due to respiration, which can be
subtracted from the motion of the electrode of which stability is
of interest.
Instantaneous fluid status, among other variables, can cause some
drift in position as measured by a localization system such as the
ENSITE.RTM. NAVX.RTM. system. An exemplary method can include a
correction factor that accounts for fluid status drift, which may
be found by comparing position of a stable electrode from one cycle
to the next and applying any measured offset to an electrode of
interest.
As described herein, for various vector metrics, subtraction
techniques or other techniques may act to reduce or eliminate fluid
status contributions or movement contributions caused by
respiration, the heart in the body (e.g., within a localization
field) or by patient movement (e.g., change in posture, etc.).
As mentioned, a particular exemplary approach uses principle
component analysis (PCA), which can rely on variations in all
electrode motions to determine cardiac axes. For example, the axis
in which the greatest amount of variation is found can be defined
as the long axis (primary contraction mechanism), the axis in which
the second greatest amount of variation is found can be defined as
the short axis (secondary contraction mechanism), and the axis in
which the third greatest amount of variation is found can be
defined as the normal axis (tertiary contraction mechanism). As
described herein, PCA may be used to uncover one or more directions
associated with respiratory motion (e.g., optionally accounting for
respiratory frequency). An exemplary method may include instructing
a patient to inhale/exhale to assist with an analysis to determine
one or more directions associated with respiratory motion (e.g., by
time marking data, providing an inhalation window, providing an
exhalation window, etc.)
An exemplary transformation method can find a "best" geometrical
fit where the sum of the orthogonal distances to the original
localization system LPS (X, Y, Z) data is minimized (see, e.g.,
naive coordinate system of FIG. 4). If V0 is the centroid position,
then:
0) V0 is the best fitted constant
1) V0+k1*V1 is the best fitted line
2) V0+k1*V1+k2*V2 is the best fitted plane
3) V0+k1*V1+k2*V2+k3*V3 is the best fitted space
where k1, k2, k3 are scalars, V1 is the LV long-axis, and V2 is the
LV short-axis.
Another approach of this analysis includes the PCA of individual
electrodes to define electrode specific long, short, and normal
axis mechanical motion of said electrodes.
FIG. 5 shows data presentations 510, 520 from conventional
echocardiographic speckle tracking analyses that track motion of
selected "speckles", which are then analyzed along the radial plane
of the heart (e.g., transverse plane). The presentation 510
corresponds to paced activation of the heart (see ECG 512) while
the presentation 510 corresponds to intrinsic activation of the
heart (see ECG 522).
As described herein, an exemplary method can transform data
acquired via a localization system that relies on one or more
indwelling electrodes to another format that provides for analyses
comparable to those of echocardiography. For example, by
transforming position information from a naive coordinate system
(NCS) to a cardiac coordinate system (CCS), the localization system
data may provide metrics comparable to echocardiographic tissue
Doppler imaging (TDI) and speckle tracking. TDI measures regional
wall motion velocities along a longitudinal axis while speckle
tracking selects point locations of myocardium to track from frame
to frame to evaluate strain, strain rate, tissue velocity, and LV
rotation as shown in FIG. 5.
As explained, a naive coordinate system (NCS) is often independent
of the orientation or motion of the heart. To better assess
electrode motion based upon separate components of motion (e.g.,
longitudinal, radial, circumferential, or x', y', and z') a cardiac
coordinate system can minimize signal attenuation due to cardiac
orientation.
Transforming localization system data into cylindrical coordinates
provides a more accurate and intuitive method of analyzing motion
data. In addition, data are more representative of current
standards for measurement of mechanical motion such as standards
associated with echocardiography.
FIG. 6 shows a diagram of an exemplary transform scheme 600 that
relies on a RV-to-LV vector. In FIG. 6, a triangle 610 is shown
with respect to the heart 102. The vertices of the triangle include
a right atrial point (RA), a right ventricular point (RV) and a
left ventricular point (LV). A diagram 620 illustrates movement of
the RV-to-LV vector during a cardiac cycle. Specifically, when the
heart 102 contracts, the vector from the RV point to the LV point
rotates in a counter-clockwise direction during systole and rotates
in clockwise direction during diastole. Trial data indicate that,
at the end of systole, length of the RV-to-LV vector reaches a
minimum while angle of rotation from delivery of a pacing stimulus
(V-pulse) reaches a maximum. In the example of FIG. 6, the diagram
620 indicates that, during a cardiac cycle, motion of the RV point
is much less than motion of the LV point. Further, data indicate
that the RA point also tends to move much less than the LV point.
Hence, length of the RA-to-RV segment of the triangle 610 varies
less during a cardiac cycle than length of the RV-to-LV segment or
the RA-to-LV segment. As described herein, by collecting data with
respect to time, waveforms are generated that exhibit physiologic
behavior. Such waveforms can be analyzed by one or more techniques
where a result or results may be relied on for diagnosis,
determining or selecting a configuration, etc.
As described herein, an exemplary method can include subtracting
right ventricular position in a 3-D coordinate system from left
ventricular position in the 3-D coordinate system, or vice versa,
to remove from the analysis movement contributions caused by
respiration, the heart itself or a combination of both respiration
and the heart itself (e.g., movement of the heart in the body).
Such a technique can also remove possible artifacts caused by body
movements such as posture changes. In various scenarios, one or
more subtraction techniques may be applied, for example, to isolate
particular movement (e.g., consider a technique that subtracts
contractile motion of a particular electrode). A centroid may also
be calculated for various points (e.g., a centroid of a triangle
defined by a RA electrode, a RV electrode and a LV electrode). In
such an example, movement of the centroid may be tracked over time
(e.g., as a centroid waveform) and analyzed to, for example,
enhance diagnosis of cardiac condition or selection of a
configuration (e.g., electrodes, timing parameters, etc.).
As shown in a block 632 of FIG. 6, for a site associated with the
right ventricle, position of this site can be represented as
Site.sub.RV=(X.sub.RV, Y.sub.RV, Z.sub.RV) and for a site
associated with the left ventricle, position of this site can be
represented as Site.sub.LV=(X.sub.LV, Y.sub.LV, Z.sub.LV). Given
the foregoing notation, as shown in a block 634 of FIG. 6, a vector
can be defined as Vector.sub.RV-LV=Site.sub.RV-Site.sub.LV. As
shown by the vector operations of a block 636 of FIG. 6, magnitude
of this vector can be calculated as:
Mag.sub.RV-LV=|Site.sub.RV-Site.sub.LV|=((X.sub.RV-X.sub.LV).sup.2+(Y.sub-
.RV-Y.sub.LV).sup.2+(Z.sub.RV-Z.sub.LV).sup.2).sup.0.5
Also shown in the block 636, vector rotational angle can be
calculated using the dot product of two vectors:
Vector.sub.RV-LVVector.sub.Ref=|Vector.sub.RV-LV.parallel.Vector.sub.Ref|-
cos .theta.
In the foregoing equation, the arc cosine function provides the
angle .theta.. As indicated in the block 636, angular velocity
.omega. can be calculated from the time derivative of the angle
(d.theta./dt) and angular acceleration from the second time
derivative of the angle (d.omega./dt). The various position data or
angle data (or derivatives or other variants thereof), where
available with respect to time, may be represented as waveforms.
Such waveforms may be analyzed, for example, by comparing waveforms
for different conditions (e.g., electrode configurations,
stimulation parameters, patient positions, activity levels, etc.).
Also in FIG. 6, a vector angles diagram 640 indicates angular
movement of a RA-to-RV vector and a RA-to-LV vector during a
cardiac cycle.
In the example of FIG. 6, the reference vector, Vector.sub.Ref, is
typically a fixed vector, for example, based on positions at a time
of (or prior to) a ventricular stimulus (e.g., V-pacing) or an
intrinsic ventricular event (e.g., R-sense) (e.g., to provide a
baseline). As described herein, any time point or points may serve
as a fiducial or fiducials in time, for example, with respect to
the cardiac cycle. As explained with respect to FIG. 6, the vector
RV-to-LV (Vector.sub.RV-LV) is a changing vector that changes in
response to contraction of the heart, whether caused by intrinsic
activity or delivery of a stimulus (e.g., as associated with a
pacing therapy).
As to an exemplary transform method, at each electrode, onset and
end of ventricular systolic motion or electrical activation may be
determined from an EGM signal (e.g., based on peak amplitude, peak
negative slope, or achieving a threshold voltage or slope, among
other techniques). The electrode positions at the time of
activation and end of systolic motion may be noted. In this
example, a transformation may occur through a series of rotation
matrices. For example, change in vector magnitude along a single
axis may be optimized (e.g., maximal RA-to-RV shortening as being
along the Z-axis). In an alternative approach, the absolute maxima
of a distance vector may be utilized to determine the cardiac
axis.
FIG. 7 shows an exemplary volume element model 700 and an exemplary
method 720 for defining a cardiac coordinate system (CCS). The
model 700 includes various volume elements 710 where each volume
element corresponds to an angular segment and an axial segment of
the heart. In the example of FIG. 7, the angular segments include
posterior, posterior superior, posterior lateral (or
posterolateral), anterior, anterior superior and anterior lateral
(or anterolateral) while the axial segments include base, mid and
apex. In the example of FIG. 7, each volume element can be
described with respect to a cylindrical CCS with coordinates Z', R
and C. Further, the collection of 16 volume elements defines a
chamber volume for the left ventricle.
The exemplary method 720 includes providing a model 724, tagging
multiple volume elements based on location of an electrode and
defining a CCS 732 based on the tagged elements. For example, using
a sectioned left ventricular model a clinician may estimate
electrode placement locations under fluoroscopic guidance to define
orientation of the model. Actual electrode locations may be
provided in a naive coordinate system associated with a
localization system, referred to as "LPS", and notated:
a.sub.x.sub.LPS, a.sub.y.sub.LPS, a.sub.z.sub.LPS
In this example, the defined location on the left ventricular model
would be
a.sub.x.sub.model, a.sub.y.sub.model, a.sub.Z.sub.model
By defining
a.sub.x.sub.LPS, a.sub.y.sub.LPS, a.sub.z.sub.LPS=a.sub.x.sub.mod
el, a.sub.y.sub.mod el, a.sub.z.sub.mod el
and solving for the inverse solution, one may calculate a rotation
matrix to transform the model axes.
FIG. 8 shows an anatomic map 800 of a venous network 810 where the
map 800 was generated using ENSITE.RTM. NAVX.RTM. software based on
position data acquired with respect to a naive coordinate system
(X, Y, Z). In this example, a data mapping procedure took less than
15 minutes, including access to three branches of the coronary
sinus and construction of the anatomic map 800. After the mapping
procedure, the catheter was removed, the LV lead was placed in a
location at the implanting clinician's discretion (see
anterolateral branch), and the device implant was completed.
FIG. 8 also shows an exemplary coordinate transformation 805. In
this example, raw naive Cartesian coordinates of the positions are
shown with respect to the X, Y, Z coordinate system where X
corresponds to "left", Y corresponds to "posterior" and Z
corresponds to "superior". Another coordinate system is shown with
respect to coordinates for a long axis (L), a short axis (S) and a
normal axis (N). Yet another coordinate system is shown with
respect to coordinates for a longitudinal axis (Z'), a radial
dimension (R) and a circumferential dimension (C).
As described herein, a coordinate transform may transform
coordinates associated with a localization system into one or more
alternative coordinate systems. For the ENSITE.RTM. NAVX.RTM.
localization system, X is from right to left, Y is from anterior to
posterior, and Z is from inferior to superior in a Cartesian system
that typically has an origin at the "belly patch" (see patch 428 of
FIG. 4). In one alternative, motions can be resolved in a Cartesian
coordinate system with the same principal directions but whose
origin is located at a different location, for example one of the
other surface patches, an intracardiac or other indwelling
electrode, or some computed stable reference point within the body.
In yet another alternative, a cardiac coordinate system may be
computed in which the naive Cartesian X, Y and Z directions
correspond with a short axis (S), a normal axis (N), and along axis
(L) of the heart. In FIG. 8, the exemplary coordinate
transformation 805 corresponds to a cylindrical cardiac coordinate
system that resolves 3-D motions to longitudinal (Z'), radial (R),
and circumferential (C) components.
A coronary sinus projection transform technique is described with
respect to the venous network 810 of FIG. 8, which shows a RV tip
electrode location and an associated vector. According to this
technique, during left ventricular (LV) lead implant, electrode
location data may be collected and fitted to an
elliptical/spherical basal model of the LV. Data collected along
the atrioventricular groove from the entrance of the coronary sinus
to the subselection of the lateral vein may be considered to be a
quadrant of a symmetrical basal model for which a basal centroid
may be defined. To determine the apical point a corrected right
ventricular electrode location may be utilized as shown with
respect to the venous network 810.
FIG. 9 shows various diagrams of the heart 900 along with
particular vector angles. In the example of FIG. 9, the superior
vena cava (SVC) is considered to be anatomically vertical and
therefore approximately parallel to the ENSITE.RTM. NAVX.RTM.
Z-axis. Accordingly, positions of an electrode passing through the
SVC may be recorded and relied on to establish a line parallel to
the Z-axis. However, depending on patch placement (see FIG. 4) this
parallelism may not be exact. To correct for such error, the
ENSITE.RTM. NAVX.RTM. Z-axis can be rotated along the single axis
to fit the data collected through the SVC. In addition to data
collection along the passage through the SVC, a lead with a pair of
electrodes incorporated proximally may also be used.
In the approach of FIG. 9, defined vertical axis angles of rotation
may be derived using the lead locations in two planes (e.g., XY and
XZ). Rotation angles may be estimated with the addition of
correction factors to estimate two angles of rotation as shown in
FIG. 9 and derivation of the cardiac axis may follow.
As described herein, the various vector metrics shown in FIG. 6 may
be recast in a cardiac coordinate system (CCS). For example, the
naive coordinate system (NCS) with Cartesian coordinates X, Y, Z
may be transformed via PCA to a cylindrical CCS with coordinate Z',
R and C. Further, an exemplary method may compare data in a
cylindrical CCS to vector data in, for example, a naive Cartesian
coordinate system.
FIG. 10 shows an exemplary ECG gating method 1000 along with
associated data plots 1010, 1020 and 1030. The method 1000 includes
a provision block 1002 that provides an electrocardiogram (e.g.,
surface or IEGM). An identification block 1004 identifies one or
more markers, for example, for a window. A determination block
1006, determines a time of peak motion based at least in part on
one or more markers of the electrocardiogram. Accordingly, an
exemplary method can include providing an electrocardiogram of a
patient; providing position information with respect to time, the
position information acquired via an electrode located in a venous
network of the patient; defining a window based on the
electrocardiogram; and analyzing the position information within
the defined window to determine a time of peak motion of the
electrode. In such a method, the analyzing can analyze the position
information with respect to a cardiac coordinate system, which may
be a cylindrical coordinate system. Such a method can enhance
accuracy in determination of a time of peak motion of the electrode
as being related to an intrinsic or paced activation of the heart.
Time of peak motion may be used to adjust a cardiac therapy.
As described herein, an exemplary method may identifying motion due
to respiration based on a predefined respiratory motion direction
in a cardiac coordinate system. For example, such a method may
include defining a respiratory motion direction by performing a
principal component analysis. An analysis may include analyzing
position information in a manner that accounts for respiratory
motion (e.g., to select certain data, to discount or adjust certain
motion, etc.). An exemplary method may include defining one or more
windows based on an electrocardiogram and respiratory motion or
respiratory motion alone.
As described herein, such an ECG gating technique can assist with
data acquisition for purposes transforming data to a cardiac
coordinate system (CCS). Dashed vertical lines indicate a time
period from the Q-wave to the T-wave in the ECG plot 1010. These
two cardiac events or features define a window in which peak points
for different motion data signals (e.g., LV circumferential motion
plot 1020 and RV circumferential motion plot 1030) were selected as
CCS parameters.
In the example of FIG. 10, CCS-based parameters depend on selection
of maximum/minimum (or "peak") points on motion waveforms such as
the waveform plots 1020 and 1030. An electrode displacement signal
of a localization system can sometimes be susceptible to a variety
of factors (electrical artifact, noise issues, field
inhomogeneities, etc.), which can cause irregular "bumps" in the
signal. Such irregularities are counterintuitive and
non-physiological in most cases. In addition, a transformation to
CCS components has the potential to create some odd morphologies in
a motion waveform. Occurrences of such morphologies can lead to
improper selection of peaks in waveform, which may lead to
inaccurate values for CCS parameters. A good amount of these false
peaks were detected in the post-systolic time period. In an effort
to limit suboptimal peak selections, CCS motion waveforms were ECG
gated. As indicated in FIG. 10, peak selection was restricted to a
window defined between the Q-wave and the onset of the T-wave.
FIG. 11 shows an exemplary plot 1110 of 3-D data acquired using a
localization system and an exemplary method 1120 for defining a
CCS. Specifically, the 3-D data are traces of electrode motion
paths of individual electrodes positioned in a patient. The method
1120 includes providing data 1124, performing a PCA based on the
provided data 1128, and defining a CCS based at least in part on
the performed PCA. The plot 1110 shows 3-D data in a naive X, Y, Z
coordinate system and a new coordinate direction (e.g., Z'-axis) in
a cardiac coordinate system. In the example of FIG. 11, the Z'
direction corresponds to motion along a "long" axis of the
heart.
FIG. 12 shows a 2-D X-ray front chest projection 1210 and a 2-D
X-ray lateral chest projection 1220 along with an overlay of a PCA
derived long axis vector. The front chest projection 1210
corresponds to a naive coordinate system ZX plane while the lateral
chest projection 1220 corresponds to the naive coordinate system YZ
plane.
FIG. 13 shows an exemplary 3-D plot 1310 with a prolate sheroid
transform model 1320 along with projection plane plots 1332, 1334
and 1336. The plot 1310 and accompanying planar projections 1332,
1334 and 1336 include a long axis (L) and a short axis (S) as well
as a normal vector (N). As described herein, once a PCA has been
performed on electrode motion data and one or more resulting
cardiac axes have been formed (e.g., L and S), the data can be
transformed from the naive coordinate system (e.g., X, Y, Z) to a
cylindrical cardiac coordinate system (Z', R, C). Specifically, as
indicated in the plot 325 of FIG. 3, the transformation can
transform the long axis (L) to the Z' dimension, the short axis (S)
to the radial dimension R and provides a circumferential angle C.
Where data are recast simply to a Cartesian coordinate system
(e.g., L, S, N), such a coordinate system may be referred to as a
Cartesian cardiac coordinate system.
In the example of FIG. 13, the Z', R and C coordinates correspond
to longitudinal, radial and circumferential motion, respectively.
These are the primary directions in which myocytes of the heart
shorten and elongate. Such a description of the mechanical behavior
of the heart is in line with the standards in imaging and therefore
easier to understand clinically, as well as physiologically (see,
e.g., echocardiography of FIG. 5).
As described herein, a PCA can uncover a major axis that represents
the long-axis of the LV, spanning from the center of the apex to
the center of the base of the chamber. Further, a PCA can uncover a
minor axis that represents the short-axis of the LV. A normal axis
may be considered as being orthogonal to both the major and minor
axes to provide a complete new 3-D coordinate system in the cardiac
space.
In the plot 1310, the CCS axes produced for this particular patient
appear to fairly accurate, anatomically, correspond to motion of
the RA, RV, and LV (CS) electrode locations. The X-rays 1210, 1220
further confirm the PCA approach via 2-D projections of the CCS
axes with sample chest X-rays from the patient, in the
anterior-posterior (AP), or frontal, view 1210 and the lateral view
1220.
As mentioned, a prolate spheroid model approach may be applied as
an alternative to PCA. Accordingly, a prolate spheroid model may be
fit to data and then a coordinate system may be extracted from the
fit model, for example, where a major axis of the prolate spheroid
is considered a Z' axis and where a minor axis of the prolate
spheroid is considered orthogonal to the Z' axis (see, e.g.,
R).
An exemplary method can include a PCA followed by fitting data to a
prolate spheroid model. For example, a PCA can determine a Z' axis
and the Z' axis may serve as a major axis of a prolate spheroid
model. Such a method may optionally fit systolic data and diastolic
data separately to provide two separate prolate spheroids (e.g., a
systolic prolate spheroid and a diastolic prolate spheroid). In
another example, data for specific points in time may be fit to
construct a time varying prolate spheroid. Such a prolate spheroid
may optionally be visualized to show variation during a cardiac
cycle. Where data are acquired for intrinsic activation and paced
activation of the heart, prolate spheroids for such activations may
be compared to understand better efficacy of the paced activation.
While intrinsic and paced activation are mentioned, other
conditions may be varied to provide distinct prolate spheroids (or
other models) that facilitate comparison of conditions.
As described herein, an exemplary method can include accessing
cardiac information acquired via a catheter located at various
positions in a venous network of a heart of a patient where the
cardiac information includes position information with respect to
time for one or more electrodes of the catheter; based on at least
some of the position information, defining a cylindrical cardiac
coordinate system; and defining a prolate spheroid in the
cylindrical cardiac coordinate system where the prolate spheroid
represents at least the left ventricle of the heart. In such a
method, a PCA may help define a long axis of the prolate spheroid
and a short axis of the prolate spheroid. In various methods, a
prolate spheroid may be defined as a time varying prolate spheroid.
In various methods, one prolate spheroid may correspond to a
condition while another prolate spheroid corresponds to a different
condition where, for example, comparing the two prolate spheroids
can help assess left ventricular function for the conditions (e.g.,
intrinsic activation of the heart and paced activation of the heart
or other conditions).
FIGS. 14, 15 and 16 show motion waveform plots 1400, 1500 and 1600,
respectively, for electrodes in a cardiac coordinate system. The
plots 1400, 1500 and 1600 include data for intrinsic activation of
the heart, right ventricular pacing, left ventricular pacing and
biventricular pacing.
Specifically, FIG. 14 shows example single cardiac cycle waveforms
of radial motion of LV distal electrode (R(t)), ensemble averaged
over recorded segment; FIG. 15 shows example single cardiac cycle
waveforms of circumferential motion of LV distal electrode (C(t)),
ensemble averaged over recorded segment; and FIG. 16 shows example
single cardiac cycle waveforms of longitudinal motion of LV distal
electrode (Z'(t)); ensemble averaged over recorded segment.
Once some evidence to validate a PCA-based CCS has been acquired, a
clinician may implement an exemplary method to transform acquired
data from a naive coordinate system (or Cartesian CCS (e.g., L, S,
N)) to a cylindrical CCS (Z', R, C). For various examples described
herein, the MATLAB.RTM. framework "cart2pol" function (The
MathWorks, Inc., Natick, Mass.) can be used to perform a
transformation to cylindrical coordinates. In addition, the angle
C, for the circumferential coordinate, can be unwrapped to avoid
+/-.pi. steps. A cylindrical CCS can yield electrode locations and
displacements in radial, circumferential, longitudinal
coordinates.
As to radial motion of the heart (see, e.g., the plots 1400 of FIG.
14), when viewing a cine of the heart over the course of the
cardiac cycle, one may readily notice and appreciate motion
radially going towards and away from the center of the chamber,
especially in a short-axis view. Therefore, the radial component of
myocardial motion is important and can be captured, to a certain
degree, by the radial motion waveforms of the LV distal electrode.
With R being the radial distance from the centroid, the systolic
contraction appears to occur at a later time during LV only pacing,
for a particular patient trial. Noting that peak-to-peak
amplitudes, or the range of contractile movement, appear to be
similar for all four modes of pacing/non-pacing for the particular
patient.
As to circumferential motion of the heart (see, e.g., the plots
1500 of FIG. 15), with the majority of the myocyte fibers oriented
in the circumferential direction, circumferential motion is
arguably the primary and most meaningful component of myocardial
motion. Circumferential motion accounts for the "twisting" and
"untwisting" action seen in systole and diastole, respectively. For
a particular patient both the BiV and LV only pacing interventions,
which have been shown in studies to have common effects, increased
the systolic peak-to-peak amplitude of circumferential motion. On
the contrary, for the patient, RV pacing appeared to delay the
contraction. Qualitatively, a smooth bell-shaped waveform from the
BiV and LV plots could be observed and appreciated as an accurate
reflection of the mechanical behavior of the myocardium.
As to longitudinal motion of the heart (see, e.g., the plots 1600
of FIG. 16), such motion can be observed in long-axis views, with
the movement originating from the apex, propagating through the
mid-ventricular region, and ending at the base. Longitudinal motion
waveforms of the LV distal electrode for a particular patient were
analyzed for intrinsic rhythm and the different pacing
interventions performed during a clinical trial. Plotted data
delineated the systolic phase in a LV only pacing, while, in
contrast, RV pacing, which is known to induce acute
intraventricular dyssynchrony, could be presumed in a RV only
pacing plot, where evidence of dyskinetic motion in the
longitudinal direction was shown (i.e., with the electrode moving
towards the apex first, then towards the base).
A particular exemplary acquisition and analysis method includes
inserting a catheter and moving the catheter from a proximal
coronary sinus location to a distal coronary sinus location and to
anterior, anterolateral, and lateral branches of the coronary
sinus. At each location, the method includes recording about 10
seconds to about 30 seconds of data, including EGMs from each
electrode at a frequency of 1200 Hz and including real-time
position data for each electrode (e.g., X, Y, Z patch coordinate
system) at a frequency of about 93 Hz (e.g., 1200/13 Hz).
Additionally, at each location, the method includes sampling
location points for a subsequent transformation process associated
with a cardiac coordinate system. After the catheter-based
procedure, the exemplary method includes inserting and placing a
conventional LV bipolar lead targeted to a particular coronary
sinus branch of the patient.
In an exemplary offline method, the structure and anatomy of the
coronary sinus for a patient (along long, short, and normal axes)
were analyzed based on data acquired during an intraoperative
procedure. In this method, the short-normal plane was aligned with
the coronary sinus proximal and distal direction (i.e. the base of
the heart), the short axis was aligned pointing toward the RV tip
electrode's projection onto the basal plane, and the long axis was
aligned pointing toward the apex, in a direction approximately
through the center of the basal plane. A cylindrical coordinate
system was then computed using the long axis as the Z' direction,
the short axis as the 0.degree. for circumferential direction (C)
and counterclockwise positive when looking base-to-apex, and radial
direction (R) measured from the long axis outward (see, e.g., FIG.
8).
With respect to cardiac mechanics, mechanical coordination between
the RV and LV, and more importantly across regions of the LV, is a
major determinant of overall pump function. Preoperative
echocardiography, including Tissue Doppler Imaging (TDI) (see
Ansalone G, Giannantoni P, Ricci R, et al.: Doppler myocardial
imaging to evaluate the effectiveness of pacing sites in patients
receiving biventricular pacing. J Am Coll Cardiol 2002; 39:489-499)
and its derivatives like Tissue Tracking Imaging (TTI) (see Pan C,
Hoffmann R, Kuhl H, et al.: Tissue tracking allows rapid and
accurate visual evaluation of left ventricular function. Eur J
Echocardiogr 2001; 2:197-202) and Tissue Synchronization Imaging
(TSI) (see Murphy R T, Sigurdsson G, Mulamalla S, et al.: Tissue
synchronization imaging and optimal left ventricular pacing site in
cardiac resynchronization therapy. Am J Cardiol 2006;
97:1615-1621), or 2-D speckle tracking methods (see Leitman M,
Lysyansky P, Sidenko S, et al.: Two-dimensional strain--A novel
software for real-time quantitative echocardiographic assessment of
myocardial function. J Am Soc Echocardiogr 2004; 17:1021-1029) can
reveal regions of late mechanical activation or hypokinesis that
negatively impact cardiac performance. However, echocardiography
does not allow one to judge accessibility of these regions via the
coronary veins. Further, TDI only gives longitudinal motion of
myocardial segments in the apical view, and speckle tracking yields
only 2-dimensional motion and strain information. Moreover, both of
these techniques have been shown to have large inter-observer
variability (Chung E S, Leon A R, Tayazzi L, et al.: Results of the
predictors of response to CRT (PROSPECT) trial. Circ 2008;
117:2608-2616).
As described herein, a localization system (e.g., the ENSITE.RTM.
NAVX.RTM. system) can record electrode motion in the coronary sinus
and branches thereof by sampling at locations accessible by a
guidewire or catheter. An exemplary method may target lead
placement to a location directly measured to have mechanical
latency. In addition to acquiring data of 3-D electrode
displacement and velocity, as mentioned, projection of data onto
computed cardiac axes allows the resolution of radial,
circumferential, and longitudinal components of cardiac motion from
a simultaneous acquisition. As described herein, an exemplary
method can use localization system derived motion to generate
waveforms reminiscent both of TDI long-axis velocity traces or TT
long-axis displacement and of 2-D speckle tracking radial
displacement or cardiac twist traces concurrently.
As to septal motion, an echocardiography parameter "Q to max
posterior movement of septum" is an M-mode measurement that
estimates the time from the onset of the Q-wave from the
electrocardiogram (ECG) to peak of the signal waveform representing
posterior movement of the septum. With respect to the transducer at
the appropriate angle, this posterior movement of the septum
corresponds to the single radial axis of motion in the M-mode
echo.
To determine an analog to the echocardiography parameter "Q to max
posterior movement of septum", a CCS parameter, "Q to peak septal
motion", was developed, according to following equation: Q to peak
septal motion=(Time of peak radial motion of RV tip
electrode)-(Time of Q-wave)
In this exemplary approach, the RV tip electrode was thought to be
the data point closest to representing the myocardial motion of the
interventricular septum.
FIG. 17 shows exemplary plots 1700 that compare CCS based septal
motion parameter and septal motion delay from echocardiography
analysis for Patients 1 and 4 of a trial assessment. The plots 1700
show, for each patient, a comparison of the CCS Q-to-peak septal
motion parameter with the time from Q to max posterior movement of
septum as assessed by M-mode echocardiography assessment. The CCS
septal motion parameter was based on the Q-wave detection and the
peak selection from ECG-gated (Q-to-T wave) radial motion of LV
electrodes (see, e.g., FIG. 10).
The plotted data for Patient 1 demonstrates a common trend between
the CCS Septal Motion time delay parameter and the equivalent echo
parameter, with respect to the various pacing interventions. The
plotted data for Patient 4 also shows a strong correlation between
the CCS parameter and the echocardiography parameter.
FIG. 18 shows an exemplary plot 1800 for delay parameters.
Specifically, the plot 1800 shows a comparison between a CCS-based
dyssynchrony parameter and an "anferolateral-to-inferoseptal basal
delay in peak velocity" from an echocardiography TDI analysis for
Patient 5 of a trial assessment. In the plot 1800, the CCS-based
dyssynchrony parameter was based on peak selections from ECG-gated
(Q-to-T wave) circumferential motion of RV and LV electrodes (see,
e.g., FIG. 10) and the echocardiography dyssynchrony parameter is
the "anferolateral-to-inferoseptal basal delay in peak velocity"
calculated from TDI, referred to simply as "Echo" in the plot
1800.
A common parameter to assess or describe cardiac mechanical
properties in heart failure (e.g., for CRT candidates) is
intraventricular dyssyncrhony. Specifically, the time delays to
peak velocities of several different myocardial segments (in a
standard 12-segment model) can be measured by echo tissue Doppler
imaging (TDI). Once these time delays are obtained, other
parameters, specifically the "anterolateral-to-inferoseptal basal
delay in peak velocity" can be calculated. This septal-to-lateral
delay is generally the standard for dyssynchrony, as it provides
the temporal difference in mechanical activation from one wall of
the LV to the opposite wall in the chamber, yielding usually the
maximum delay.
While dyssynchrony parameters can be computed in a standard or
naive coordinate system (e.g., of the ENSITE.RTM. NAVX.RTM. system)
using magnitude displacements of RV and LV electrodes, a CCS-based
approach allows a dyssynchrony value to be derived from RV and LV
motion along directions that are physiologically more meaningful
and indicative of the tissue motion, rather than the electrode
motion. An exemplary equation follows that was used to compute a
CCS-based dyssynchrony parameter: Delay=(Time to peak
circumferential motion on LV distal electrode)-(Time to peak
circumferential motion on RV distal electrode)
where, "+" sign=RV activated first, and "-" sign=LV activated
first
Circumferential motion is shown in the foregoing equation by
default, since the fibers in the midwall of the myocardium are
oriented primarily in the circumferential direction. As described
herein, as an alternative, longitudinal motion can be used, which
may correlate better with the echo parameter (i.e., as it is based
on the long-axis inherent in TDI).
FIG. 19 shows an exemplary method 1900 for adjusting a therapy
based at least in part on a CCS-based parameter. The method 1900
includes an acquisition block 1904 that acquires information with
respect to a naive coordinate system. In a determination block
1908, the method 1900 determines a cardiac coordinate system based
at least in part on the acquired information. In one or more
subsequent determination blocks 1910, 1912, the method 1900
determines one or more parameters, which may be analogs to
echocardiography or other conventional cardiac assessment
parameters. In an adjustment block 1916, the method 1900 adjusts a
therapy based at least in part on a determined parameter. In the
example of FIG. 19, the septal parameter of block 1910 may be
determined based on the foregoing Q to peak septal motion equation
and the delay parameter of block 1912 may be determined based on
the foregoing dyssynchrony (delay) parameter.
As described herein, an exemplary method that includes transforming
localization system data into cylindrical coordinates provides a
more accurate and intuitive method of analyzing and representing
the localization system data. In addition, this data is more
representative to the current clinical standard for measuring
hemodynamic function and mechanical motion of the heart;
echocardiography outside of cardiac MRI which has a number of
inherent limitations including low frame rate acquisition, high
cost, time consuming, and complex analysis.
As described herein, comparable analysis that may be developed
using the transformed cardiac coordinate data includes M-mode, TDI
and speckle tracking. TDI measures regional wall motion velocities
along a longitudinal axis and speckle tracking which selects point
locations of myocardium to track from frame to frame to evaluate
strain, strain rate, tissue velocity, and LV rotation.
While using purely native localization system derived data may be
appropriate when analyzing any Euclidean distance between two
points, it is does not allow analysis of data in terms of component
based analysis (motion along any independent X, Y, or Z axis or
corresponding planes).
As described herein, an exemplary method of validating localization
system data derived cardiac performance indices (e.g., metrics) by
reference to comparable echocardiographic parameters includes
transforming the localization system data to projections onto a
specific axis or plane, as associated with an echocardiographic
system. Physicians are accustomed to visualizing the heart in
short-axis and long-axis when considering heart motion.
Accordingly, transforming localization system acquired motion data
to a CCS will facilitate interpretation and provide for quicker
adaptation of techniques presented herein (e.g., a format familiar
to physicians currently using other imaging modalities, such as
echocardiography). A particular CCS provides relevance to the
localization system motion data with respect to different
directions and a physiological reference for analysis is provided
by transforming the data into cylindrical coordinates (i.e., a
coordinate system that corresponds physiologically to the
orientation of ventricular fibers and mechanics).
As to transformation of coordinates, a series of rotation matrices
can be used that affect vector magnitude along a single axis, which
may be optimized (e.g., maximal RA-RV shortening along the z axis).
In another approach, absolute maxima of a distance vector may be
utilized to determine a cardiac axis. A particular exemplary
approach uses principle component analysis (PCA), which can rely on
variations in all electrode motions to determine cardiac axes. For
example, the axis in which the greatest amount of variation is
found can be defined as the long axis (primary contraction
mechanism), the axis in which the second greatest amount of
variation is found can be defined as the short axis (secondary
contraction mechanism), and the axis in which the third greatest
amount of variation is found can be defined as the normal axis
(tertiary contraction mechanism). Such an approach was applied to
acquired motion data to generate the L, S, N axes shown in FIGS. 8
and 13.
An exemplary approach can include location tagging, for example,
where by a sectioned left ventricular model, the physician is able
to estimate electrode placement locations under fluoroscopic
guidance in order to define the orientation of the model. An
exemplary approach can include coronary sinus projection. For
example, during left ventricular (LV) lead implant, electrode
location data may be collected and fitted to an
elliptical/spherical basal model of the LV. An exemplary approach
may rely on vector angles, for example, determined based on the
superior vena cava (SVC) being considered as defining an axis.
While various examples described here rely, at present, on export
and post-processing of data associated with location, an exemplary
software program loaded into a localization system can enable such
maps to be generated in near real-time (e.g., depending on memory,
processors, etc.). An exemplary mapping module may be integrated
fully into the ENSITE.RTM. NAVX.RTM. system in the same manner of
other currently available maps (LAT, Peak Voltage, CFE, etc).
Further, while the ENSITE.RTM. NAVX.RTM. system is currently
configured as a product with a cart containing amplifiers and
patient connections and another cart containing a workstation and
software, the technology may be packaged differently, for example
as a smaller (8-16 channel, versus the current 64 channel)
amplifier rack built in to a laptop or programmer-like computer
with appropriate software. Thus it becomes feasible to use such a
system in real-time during CRT implant on a routine basis.
As mentioned, an exemplary method may include determining one or
more distances (e.g., distance metrics) in an exemplary cardiac
coordinate system (CCS). For example, a method may include mapping
distance metrics based at least in part on distances between the
various locations and an anatomical feature. In this example, the
anatomical feature may be a feature of the heart such as, but not
limited to, the right atrium, the right ventricle, the ostium of
the coronary sinus, a valve of the heart, the apex of the heart and
the base of the heart. In another example, an anatomical feature
may be a nerve, such as, but not limited to, a phrenic nerve (e.g.,
to avoid phrenic nerve stimulation or to optionally stimulate the
phrenic nerve, for example, as part of a respiratory therapy such
as a sleep apnea therapy).
As described herein, various exemplary methods may be optionally
performed using a robotic system. For example, a robotic system may
be programmed with a score model and a list of parameters or
conditions to vary as well as a number of sites to investigate. To
initiate the robotic exploration, a clinician may position a lead
in a tributary and then allow the robotic system to maneuver the
lead (e.g., a few centimeters) forward, backward, etc., until it
determines an optimal site. Depending on the number of sites
investigated and variation in parameters or conditions, such a
process may be performed in a matter of minutes. For example, where
four sites are investigated in a selected vein and tested with
intrinsic and paced activation, the latter for three VV delays,
with 10 acquisitions per variation, for a heart rate of about 60
bpm, acquisition and analysis for the 16 combinations of the
process may take around 5 minutes. As described herein, the
exemplary external programmer of FIG. 20 optionally includes a
robotic mechanism to maneuver a lead in a vein and associated
exemplary control logic to perform an acquisition and analysis
process to arrive at an optimal site.
Further details on vector-magnitude based metrics are provided in
U.S. patent application Ser. No. 12/621,373 (assigned in its
entirety to Pacesetter, Inc.), titled "Cardiac Resynchronization
Therapy Optimization Using Vector Measurements Obtained from
Realtime Electrode Position Tracking," the disclosure of which is
hereby incorporated by reference.
Further details on area based metrics and volume based metrics are
provided in U.S. patent application Ser. No. 12/398,460 (assigned
in its entirety to Pacesetter, Inc.), titled "Cardiac
Resynchronization Therapy Optimization Using Parameter Estimation
from Realtime Electrode Motion Tracking," the disclosure of which
is hereby incorporated by reference.
Further details on mechanical dyssynchrony based metrics are
provided in U.S. patent application Ser. No. 12/476,043 (assigned
in its entirety to Pacesetter, Inc.), titled "Cardiac
Resynchronization Therapy Optimization Using Mechanical
Dyssynchrony and Shortening Parameters from Realtime Electrode
Motion Tracking," the disclosure of which is hereby incorporated by
reference.
Further details on electrical and mechanical activation based
metrics are provided in U.S. patent application Ser. No. 12/416,771
(assigned in its entirety to Pacesetter, Inc.), titled "Cardiac
Resynchronization Therapy Optimization Using Electromechanical
Delay from Realtime Electrode Motion Tracking," the disclosure of
which is hereby incorporated by reference.
Details on IEGM metrics corresponding to myocardial infarction and
scarring are provided in U.S. patent application Ser. No.
12/639,788 (assigned in its entirety to Pacesetter, Inc.), titled
"Methods to Identify Damaged or Scarred Tissue Based on Position
Information and Physiological Information," the disclosure of which
is hereby incorporated by reference.
Details on energy drain metrics corresponding to myocardial
infarction and scarring are provided in U.S. patent application
Ser. No. 12/553,413 (assigned in its entirety to Pacesetter, Inc.),
titled "Pacing, Sensing and Other Parameter Maps Based on
Localization System Data," the disclosure of which is hereby
incorporated by reference.
Details on stability metrics corresponding to myocardial infarction
and scarring are provided in U.S. patent application Ser. No.
12/562,003 (assigned in its entirety to Pacesetter, Inc.), titled
"Electrode and Lead Stability Indexes and Stability Maps Based on
Localization System Data," the disclosure of which is hereby
incorporated by reference.
Exemplary External Programmer
FIG. 20 illustrates pertinent components of an external programmer
2000 for use in programming an implantable medical device 100 (see,
e.g., FIGS. 1 and 2). The external programmer 2000 optionally
receives information from other diagnostic equipment 2150, which
may be a computing device capable of acquiring motion information
related to cardiac mechanics. For example, the equipment 2150 may
include a computing device to deliver current and to measure
potentials using a variety of electrodes including at least one
electrode positionable in the body (e.g., in a vessel, in a chamber
of the heart, within the pericardium, etc.). Equipment may include
a lead for chronic implantation or a catheter for temporary
implantation in a patient's body. Equipment may allow for
acquisition of respiratory motion and aid the programmer 2000 in
distinguishing respiratory motion from cardiac.
Briefly, the programmer 2000 permits a clinician or other user to
program the operation of the implanted device 100 and to retrieve
and display information received from the implanted device 100 such
as IEGM data and device diagnostic data. Where the device 100
includes a module such as the position/metrics module 239, then the
programmer 2000 may instruct the device 100 to measure potentials
associated with position or to determine metrics and to communicate
such information to the programmer via a communication link 2153.
The programmer 2000 may also instruct a device or diagnostic
equipment to deliver current to generate one or more potential
fields within a patient's body where the implantable device 100 may
be capable of measuring potentials associated with the
field(s).
The external programmer 2000 may be configured to receive and
display ECG data from separate external ECG leads 2232 that may be
attached to the patient. The programmer 2000 optionally receives
ECG information from an ECG unit external to the programmer 2000.
The programmer 2000 may use techniques to account for
respiration.
Depending upon the specific programming, the external programmer
2000 may also be capable of processing and analyzing data received
from the implanted device 100 and from ECG leads 2232 to, for
example, render diagnosis as to medical conditions of the patient
or to the operations of the implanted device 100. As noted, the
programmer 2000 is also configured to receive data representative
of conduction time delays from the atria to the ventricles and to
determine, therefrom, an optimal or preferred configuration for
pacing. Further, the programmer 2000 may receive information such
as ECG information, IEGM information, information from diagnostic
equipment, etc., and determine one or more metrics for optimizing
therapy.
Considering the components of programmer 2000, operations of the
programmer are controlled by a CPU 2202, which may be a generally
programmable microprocessor or microcontroller or may be a
dedicated processing device such as an application specific
integrated circuit (ASIC) or the like. Software instructions to be
performed by the CPU 2202 are accessed via an internal bus 2204
from a read only memory (ROM) 2206 and random access memory 2230.
Additional software may be accessed from a hard drive 2208, floppy
drive 2210, and CD ROM drive 2212, or other suitable permanent or
removable mass storage device. Depending upon the specific
implementation, a basic input output system (BIOS) is retrieved
from the ROM 2206 by CPU 2202 at power up. Based upon instructions
provided in the BIOS, the CPU 2202 "boots up" the overall system in
accordance with well-established computer processing
techniques.
Once operating, the CPU 2202 displays a menu of programming options
to the user via an LCD display 2114 or other suitable computer
display device. To this end, the CPU 2202 may, for example, display
a menu of specific programming parameters of the implanted device
100 to be programmed or may display a menu of types of diagnostic
data to be retrieved and displayed. In response thereto, the
clinician enters various commands via either a touch screen 2116
overlaid on the LCD display or through a standard keyboard 2118
supplemented by additional custom keys 2120, such as an emergency
VVI (EVVI) key. The EVVI key sets the implanted device to a safe
VVI mode with high pacing outputs. This ensures life sustaining
pacing operation in nearly all situations but by no means is it
desirable to leave the implantable device in the EVVI mode at all
times.
With regard to mapping of metrics (e.g., for patterns of
conduction), the CPU 2202 includes a 3-D mapping system 2247 and an
associated data analysis system 2249. The systems 2247 and 2249 may
receive position information and physiological information from the
implantable device 100 and/or diagnostic equipment 2150. The data
analysis system 2249 optionally includes control logic to associate
information and to make one or more conclusions based on metrics,
for example, for planning an implant procedure or, more generally,
to optimize delivery of therapy (e.g., to optimize a pacing
configuration). The system 2247 and 2249 may include features for
analyzing information to define a cardiac coordinate system (see,
e.g., the method 300 of FIG. 3).
Where information is received from the implanted device 100, a
telemetry wand 2228 may be used. Other forms of wireless
communication exist as well as forms of communication where the
body is used as a "wire" to communicate information from the
implantable device 100 to the programmer 2000.
If information is received directly from diagnostic equipment 2150,
any appropriate input may be used, such as parallel 10 circuit 2240
or serial 10 circuit 2242. Motion information received via the
device 100 or via other diagnostic equipment 2150 may be analyzed
using the mapping system 2247. In particular, the mapping system
2247 (e.g., control logic) may identify positions within the body
of a patient and associate such positions with one or more
electrodes where such electrodes may be capable of delivering
stimulation energy to the heart, performing other actions or be
associated with one or more sensors.
A communication interface 2245 optionally allows for wired or
wireless communication with diagnostic equipment 2150 or other
equipment (e.g., equipment to ablate or otherwise treat a patient).
The communication interface 2245 may be a network interface
connected to a network (e.g., intranet, Internet, etc.).
A map or model of cardiac information may be displayed using
display 2114 based, in part, on 3-D heart information and
optionally 3-D torso information that facilitates interpretation of
information. Such 3-D information may be input via ports 2240,
2242, 2245 from, for example, a database, a 3-D imaging system, a
3-D location digitizing apparatus (e.g., stereotactic localization
system with sensors and/or probes) capable of digitizing the 3-D
location. While 3-D information and localization are mentioned,
information may be provided with fewer dimensions (e.g., 1-D or
2-D). For example, where motion in one dimension is insignificant
to one or more other dimensions, then fewer dimensions may be used,
which can simplify procedures and reduce computing requirements of
a programmer, an implantable device, etc. The programmer 2000
optionally records procedures and allows for playback (e.g., for
subsequent review). For example, a heart map and all of the
electrical activation data, mechanical activation data, etc., may
be recorded for subsequent review, perhaps if an electrode needs to
be repositioned or one or more other factors need to be changed
(e.g., to achieve an optimal configuration). Electrodes may be lead
based or non-lead based, for example, an implantable device may
operate as an electrode and be self powered and controlled or be in
a slave-master relationship with another implantable device (e.g.,
consider a satellite pacemaker, etc.). An implantable device may
use one or more epicardial electrodes.
Once all pacing leads are mounted and all pacing devices are
implanted (e.g., master pacemaker, satellite pacemaker,
biventricular pacemaker), the various devices are optionally
further programmed.
The telemetry subsystem 2222 may include its own separate CPU 2224
for coordinating the operations of the telemetry subsystem. In a
dual CPU system, the main CPU 2202 of programmer communicates with
telemetry subsystem CPU 2224 via internal bus 2204. Telemetry
subsystem additionally includes a telemetry circuit 2226 connected
to telemetry wand 2228, which, in turn, receives and transmits
signals electromagnetically from a telemetry unit of the implanted
device. The telemetry wand is placed over the chest of the patient
near the implanted device 100 to permit reliable transmission of
data between the telemetry wand and the implanted device.
Typically, at the beginning of the programming session, the
external programming device 2000 controls the implanted device(s)
100 via appropriate signals generated by the telemetry wand to
output all previously recorded patient and device diagnostic
information. Patient diagnostic information may include, for
example, motion information (e.g., cardiac, respiratory, etc.)
recorded IEGM data and statistical patient data such as the
percentage of paced versus sensed heartbeats. Device diagnostic
data includes, for example, information representative of the
operation of the implanted device such as lead impedances, battery
voltages, battery recommended replacement time (RRT) information
and the like.
Data retrieved from the implanted device(s) 100 can be stored by
external programmer 2000 (e.g., within a random access memory (RAM)
2230, hard drive 2208, within a floppy diskette placed within
floppy drive 2210). Additionally, or in the alternative, data may
be permanently or semi-permanently stored within a compact disk
(CD) or other digital media disk, if the overall system is
configured with a drive for recording data onto digital media
disks, such as a write once read many (WORM) drive. Where the
programmer 2000 has a communication link to an external storage
device or network storage device, then information may be stored in
such a manner (e.g., on-site database, off-site database, etc.).
The programmer 2000 optionally receives data from such storage
devices.
A typical procedure may include transferring all patient and device
diagnostic data stored in an implanted device 100 to the programmer
2000. The implanted device(s) 100 may be further controlled to
transmit additional data in real time as it is detected by the
implanted device(s) 100, such as additional motion information,
IEGM data, lead impedance data, and the like. Additionally, or in
the alternative, telemetry subsystem 2222 receives ECG signals from
ECG leads 2232 via an ECG processing circuit 2234. As with data
retrieved from the implanted device 100, signals received from the
ECG leads are stored within one or more of the storage devices of
the programmer 2000. Typically, ECG leads output analog electrical
signals representative of the ECG. Accordingly, ECG circuit 2234
includes analog to digital conversion circuitry for converting the
signals to digital data appropriate for further processing within
programmer 2000. Depending upon the implementation, the ECG circuit
2243 may be configured to convert the analog signals into event
record data for ease of processing along with the event record data
retrieved from the implanted device. Typically, signals received
from the ECG leads 2232 are received and processed in real
time.
Thus, the programmer 2000 is configured to receive data from a
variety of sources such as, but not limited to, the implanted
device 100, the diagnostic equipment 2150 and directly or
indirectly via external ECG leads (e.g., subsystem 2222 or external
ECG system). The diagnostic equipment 2150 includes wired 2154
and/or wireless capabilities 2152 which optionally operate via a
network that includes the programmer 2000 and the diagnostic
equipment 2150 or data storage associated with the diagnostic
equipment 2150.
Data retrieved from the implanted device(s) 100 typically includes
parameters representative of the current programming state of the
implanted devices. Under the control of the clinician, the external
programmer displays the current programming parameters and permits
the clinician to reprogram the parameters. To this end, the
clinician enters appropriate commands via any of the aforementioned
input devices and, under control of CPU 2202, the programming
commands are converted to specific programming parameters for
transmission to the implanted device 100 via telemetry wand 2228 to
thereby reprogram the implanted device 100 or other devices, as
appropriate.
Prior to reprogramming specific parameters, the clinician may
control the external programmer 2000 to display any or all of the
data retrieved from the implanted device 100, from the ECG leads
2232, including displays of ECGs, IEGMs, statistical patient
information (e.g., via a database or other source), diagnostic
equipment 2150, etc. Any or all of the information displayed by
programmer may also be printed using a printer 2236.
A wide variety of parameters may be programmed by a clinician. In
particular, for CRT, the AV delay and the VV delay of the implanted
device(s) 100 are set to optimize cardiac function. In one example,
the VV delay is first set to zero while the AV delay is adjusted to
achieve the best possible cardiac function, optionally based on
motion information. Then, VV delay may be adjusted to achieve still
further enhancements in cardiac function.
Programmer 2000 optionally includes a modem to permit direct
transmission of data to other programmers via the public switched
telephone network (PSTN) or other interconnection line, such as a
T1 line or fiber optic cable. Depending upon the implementation,
the modem may be connected directly to internal bus 2204 may be
connected to the internal bus via either a parallel port 2240 or a
serial port 2242.
Other peripheral devices may be connected to the external
programmer via the parallel port 2240, the serial port 2242, the
communication interface 2245, etc. Although one of each is shown, a
plurality of input output (IO) ports might be provided. A speaker
2244 is included for providing audible tones to the user, such as a
warning beep in the event improper input is provided by the
clinician. Telemetry subsystem 2222 additionally includes an analog
output circuit 2246 for controlling the transmission of analog
output signals, such as IEGM signals output to an ECG machine or
chart recorder.
With the programmer 2000 configured as shown, a clinician or other
user operating the external programmer is capable of retrieving,
processing and displaying a wide range of information received from
the ECG leads 2232, from the implanted device 100, the diagnostic
equipment 2150, etc., and to reprogram the implanted device 100 or
other implanted devices if needed. The descriptions provided herein
with respect to FIG. 20 are intended merely to provide an overview
of the operation of programmer and are not intended to describe in
detail every feature of the hardware and software of the device and
is not intended to provide an exhaustive list of the functions
performed by the device 2000. Other devices, particularly computing
devices, may be used.
CONCLUSION
Although exemplary methods, devices, systems, etc., have been
described in language specific to structural features and/or
methodological acts, it is to be understood that the subject matter
defined in the appended claims is not necessarily limited to the
specific features or acts described. Rather, the specific features
and acts are disclosed as exemplary forms of implementing the
claimed methods, devices, systems, etc.
* * * * *